OpenCvSharp

The X component of the normalized vector collinear to the line

The Y component of the normalized vector collinear to the line

X-coordinate of some point on the line

Y-coordinate of some point on the line

Initializes this object

The X component of the normalized vector collinear to the line The Y component of the normalized vector collinear to the line Z-coordinate of some point on the line Z-coordinate of some point on the line

Initializes by cvFitLine output

The returned value from cvFitLineparam>

Returns the distance between this line and the specified point

Fits this line to the specified size (for drawing)

Width of fit size Height of fit size 1st edge point of fitted line 2nd edge point of fitted line

A 3-dimensional line object

The X component of the normalized vector collinear to the line

The Y component of the normalized vector collinear to the line

The Z component of the normalized vector collinear to the line

X-coordinate of some point on the line

Y-coordinate of some point on the line

Z-coordinate of some point on the line

Initializes this object

The X component of the normalized vector collinear to the line The Y component of the normalized vector collinear to the line The Z component of the normalized vector collinear to the line Z-coordinate of some point on the line Z-coordinate of some point on the line Z-coordinate of some point on the line

Initializes by cvFitLine output

The returned value from cvFitLineparam>

Returns the distance between this line and the specified point

ベクトルの外積

ベクトルの長さ(原点からの距離)

2点間(2ベクトル)の距離

Various SURF algorithm parameters

Field data

false means basic descriptors (64 elements each), true means _extended descriptors (128 elements each)

Only features with keypoint.hessian larger than that are extracted. good default value is ~300-500 (can depend on the average local contrast and sharpness of the image). user can further filter out some features based on their hessian values and other characteristics

The number of octaves to be used for extraction. With each next octave the feature size is doubled (3 by default)

The number of layers within each octave (4 by default)

Creates SURF default parameters

Only features with keypoint.hessian larger than that are extracted. false means basic descriptors (64 elements each), true means _extended descriptors (128 elements each)

Creates a new object that is a copy of the current instance.

A new object that is a copy of this instance.

tree node

Default constructor

Initializes from native pointer

struct CvTreeNode*

Initializes from native pointer

struct CvTreeNode*

sizeof(CvTreeNode)

miscellaneous flags

size of sequence header

previous sequence

next sequence

2nd previous sequence

2nd next sequence

Adds new node to the tree

The parent node that is already in the tree. The top level node. If parent and frame are the same, v_prev field of node is set to null rather than parent.

Removes node from tree

The top level node. If node->v_prev = null and node->h_prev is null (i.e. if node is the first child of frame), frame->v_next is set to node->h_next (i.e. the first child or frame is changed).

Gathers all node pointers to the single sequence

Header size of the created sequence (sizeof(CvSeq) is the most used value). Container for the sequence.

Type information

Default constructor

Initializes from native pointer

struct CvTypeInfo*

sizeof(CvTypeInfo)

not used

previous registered type in the list

next registered type in the list

type name, written to file storage

checks if the passed object belongs to the type

releases object (memory etc.)

reads object from file storage

writes object to file storage

creates a copy of the object

Registers new type

Locality Sensitive Hash (LSH) table

Track whether Dispose has been called

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct in-memory LSH table, with n bins.

Initializes from pointer

struct CvLSH*

Initializes from pointer

struct CvLSH*

Clean up any resources being used.

If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed.

Add vectors to the LSH structure, optionally returning indices.

Query the LSH n times for at most k nearest points; data is n x d, indices and dist are n x k. At most emax stored points will be accessed.

Free the given LSH structure.

Remove vectors from LSH, as addressed by given indices.

Return the number of vectors in the LSH.

number of vectors

field data

Constructor

Specifies whether this object contains the same members as the specified Object.

The Object to test. This method returns true if obj is the same type as this object and has the same members as this object.

Compares two CvPoint objects. The result specifies whether the members of each object are equal.

A Point to compare. A Point to compare. This operator returns true if the members of left and right are equal; otherwise, false.

Compares two CvPoint objects. The result specifies whether the members of each object are unequal.

A Point to compare. A Point to compare. This operator returns true if the members of left and right are unequal; otherwise, false.

Specifies whether this object contains the same members as the specified Object.

The Object to test. This method returns true if obj is the same type as this object and has the same members as this object.

Returns a hash code for this object.

An integer value that specifies a hash value for this object.

Converts this object to a human readable string.

A string that represents this object.

Creates a new object that is a copy of the current instance.

A new object that is a copy of this instance.

CvBGCodeBookModel

Track whether Dispose has been called

Initialize from pointer

struct CvBGCodeBookModel*

Allocates BGCodeBookModel structure

Clean up any resources being used.

sizeof(CvBGCodeBookModel)

CvBGCodeBookElem

Initialize from pointer

CvBGCodeBookElem*

sizeof(CvBGCodeBookElem)

CvLevMarq

Track whether Dispose has been called

Clean up any resources being used.

CvLevMarq

Track whether Dispose has been called

CV_NUM_FACE_ELEMENTS

Initialize from pointer

struct CvFaceTracker*

Clean up any resources being used.

structure contains the bounding box and confidence level for detected object

Track whether Dispose has been called

load trained detector from a file

Initializes from pointer

struct CvLatentSvmDetector*

Initializes from pointer

struct CvLSH*

Clean up any resources being used.

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

image to detect objects in memory storage to store the resultant sequence of the object candidate rectangles

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

image to detect objects in memory storage to store the resultant sequence of the object candidate rectangles threshold for the non-maximum suppression algorithm = 0.5f [here will be the reference to original paper]

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

Qt Font structure

Create the font to be used to draw text on an image

Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used.

Create the font to be used to draw text on an image

Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity.

Create the font to be used to draw text on an image

Clean up any resources being used.

Managed wrapper of all OpenCV functions

Reconstructs the original vectors from the projection coefficients

The input data; in the same format as result in cvProjectPCA. The mean (average) vector. If it is a single-row vector, it means that the output vectors are stored as rows of result; otherwise, it should be a single-column vector, then the vectors are stored as columns of result. The eigenvectors (principal components); one vector per row. The output matrix of reconstructed vectors.

Calculates up-right bounding rectangle of point set.

Either a 2D point set, represented as a sequence (CvSeq, CvContour) or vector (CvMat) of points, or 8-bit single-channel mask image (CvMat, IplImage), in which non-zero pixels are considered.

Calculates up-right bounding rectangle of point set.

Either a 2D point set, represented as a sequence (CvSeq, CvContour) or vector (CvMat) of points, or 8-bit single-channel mask image (CvMat, IplImage), in which non-zero pixels are considered. The update flag

Calculates up-right bounding rectangle of point set.

An IEnumerable<CvPoint> object (ex. CvPoint[], List<CvPoint>, ....)

Finds box vertices

Box Array of vertices

Modification of a previous sparse optical flow algorithm to calculate affine flow

Calculates the histogram of one single-channel image. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

A Source image (though, you may pass CvMat** as well). Reference to the histogram.

Calculates the histogram of one single-channel image. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

A Source image (though, you may pass CvMat** as well). Reference to the histogram. Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online.

Calculates the histogram of one single-channel image. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Calculates the histogram of single-channel images. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Source images (though, you may pass CvMat** as well), all are of the same size and type. Reference to the histogram.

Calculates the histogram of single-channel images. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Source images (though, you may pass CvMat** as well), all are of the same size and type. Reference to the histogram. Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online.

Calculates the histogram of single-channel images. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Calculates back projection

Source images (though you may pass CvMat** as well), all are of the same size and type Destination back projection image of the same type as the source images. Histogram.

Calculates back projection

Source images (though you may pass CvMat** as well), all are of the same size and type Destination back projection image of the same type as the source images. Histogram.

Locates a template within image by histogram comparison

Source images (though you may pass CvMat** as well), all are of the same size and type Destination image. Size of patch slid though the source images. Histogram. Compasion method, passed to cvCompareHist (see description of that function). Normalization factor for histograms, will affect normalization scale of destination image, pass 1. if unsure.

Locates a template within image by histogram comparison

Calculates bayesian probabilistic histograms

Calculates covariation matrix of the set of vectors

The input vectors. They all must have the same type and the same size. The vectors do not have to be 1D, they can be 2D (e.g. images) etc. The output covariation matrix that should be floating-point and square. The input or output (depending on the flags) array - the mean (average) vector of the input vectors. The operation flags

Calculates the covariance matrix for a group of input objects.

Number of source objects. Pointer to the read callback function. Input/output flags. Input/output buffer size. Pointer to the input/output buffer. Pointer to the structure that contains all necessary data for the callback functions. Averaged object. Covariance matrix. An output parameter; must be allocated before the call.

Calculates the covariance matrix for a group of input objects. (ioFlags = CV_EIGOBJ_NO_CALLBACK)

Array of IplImage input objects. Averaged object. Covariance matrix. An output parameter; must be allocated before the call.

Calculates the decomposition coefficient of an input object.

Input object. Eigen object. Averaged object. decomposition coefficient

Calculates the orthonormal eigen basis and the averaged object for group a of input objects. (ioFlags = CV_EIGOBJ_NO_CALLBACK)

Pointer to the array of IplImage input objects. Pointer to the array of eigen objects. Input/output buffer size in bytes. The size is zero if unknown. Criteria that determine when to stop the calculation of eigen objects. Averaged object. Pointer to the eigenvalues array in the descending order; may be null.

Calculates the orthonormal eigen basis and the averaged object for group a of input objects. (ioFlags = CV_EIGOBJ_OUTPUT_CALLBACK)

nObjects – Number of source objects. Pointer to the array of IplImage input objects. Pointer to the write callback function. Input/output buffer size in bytes. The size is zero if unknown. Pointer to the structure that contains all of the necessary data for the callback functions. Criteria that determine when to stop the calculation of eigen objects. Averaged object. Pointer to the eigenvalues array in the descending order; may be null.

Calculates the orthonormal eigen basis and the averaged object for group a of input objects. (ioFlags = CV_EIGOBJ_INPUT_CALLBACK)

nObjects – Number of source objects. Pointer to the read callback function. Pointer to the array of eigen objects. Input/output buffer size in bytes. The size is zero if unknown. Pointer to the structure that contains all of the necessary data for the callback functions. Criteria that determine when to stop the calculation of eigen objects. Averaged object. Pointer to the eigenvalues array in the descending order; may be null.

Calculates the orthonormal eigen basis and the averaged object for group a of input objects.

nObjects – Number of source objects. Pointer to the read callback function. Pointer to the write callback function. Input/output flags. Input/output buffer size in bytes. The size is zero if unknown. Pointer to the structure that contains all of the necessary data for the callback functions. Criteria that determine when to stop the calculation of eigen objects. Averaged object. Pointer to the eigenvalues array in the descending order; may be null.

Computes "minimal work" distance between two weighted point configurations.

First signature, size1×dims+1 floating-point matrix. Each row stores the point weight followed by the point coordinates. The matrix is allowed to have a single column (weights only) if the user-defined cost matrix is used. Second signature of the same format as signature1, though the number of rows may be different. The total weights may be different, in this case an extra "dummy" point is added to either signature1 or signature2. Metrics used The user-defined distance function. It takes coordinates of two points and returns the distance between the points. The user-defined size1×size2 cost matrix. At least one of cost_matrix and distance_func must be NULL. Also, if a cost matrix is used, lower boundary (see below) can not be calculated, because it needs a metric function.

Computes "minimal work" distance between two weighted point configurations.

Calculates global motion orientation of some selected region

Motion gradient orientation image; calculated by the function cvCalcMotionGradient. Mask image. It may be a conjunction of valid gradient mask, obtained with cvCalcMotionGradient and mask of the region, whose direction needs to be calculated. Motion history image Current time in milliseconds or other units, it is better to store time passed to cvUpdateMotionHistory before and reuse it here, because running cvUpdateMotionHistory and cvCalcMotionGradient on large images may take some time. Maximal duration of motion track in milliseconds, the same as in cvUpdateMotionHistory.

Calculates homography matrix for oblong planar object (e.g. arm)

The main object axis direction (vector (dx,dy,dz)). Object center ((cx,cy,cz)). Intrinsic camera parameters (3x3 matrix). Output homography matrix (3x3).

Calculates the histogram of one single-channel image. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Source image. Reference to the histogram.

Calculates the histogram of one single-channel image. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Source image. Reference to the histogram. Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online.

Calculates the histogram of one single-channel image. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Calculates the histogram of single-channel images. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Source images, all are of the same size and type. Reference to the histogram.

Calculates the histogram of single-channel images. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Source images, all are of the same size and type. Reference to the histogram. Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online.

Calculates the histogram of single-channel images. The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images.

Computes d(AB)/dA and d(AB)/dB

Calculates gradient orientation of motion history image

Motion history image Mask image; marks pixels where motion gradient data is correct. Output parameter. Motion gradient orientation image; contains angles from 0 to ~360°. The function finds minimum (m(x,y)) and maximum (M(x,y)) mhi values over each pixel (x,y) neihborhood and assumes the gradient is valid only if min(delta1,delta2) <= M(x,y)-m(x,y) <= max(delta1,delta2). The function finds minimum (m(x,y)) and maximum (M(x,y)) mhi values over each pixel (x,y) neihborhood and assumes the gradient is valid only if min(delta1,delta2) <= M(x,y)-m(x,y) <= max(delta1,delta2).

Calculates gradient orientation of motion history image

Calculates optical flow for two images by block matching method

First image, 8-bit, single-channel. Second image, 8-bit, single-channel. Size of basic blocks that are compared. Block coordinate increments. Size of the scanned neighborhood in pixels around block. Uses previous (input) velocity field. Horizontal component of the optical flow of floor((prev->width - block_size.width)/shiftSize.width) × floor((prev->height - block_size.height)/shiftSize.height) size, 32-bit floating-point, single-channel. Vertical component of the optical flow of the same size velx, 32-bit floating-point, single-channel.

Estimate optical flow for each pixel using the two-frame G. Farneback algorithm

Computes flow for every pixel of the first input image using Horn & Schunck algorithm

First image, 8-bit, single-channel. Second image, 8-bit, single-channel. Uses previous (input) velocity field. Horizontal component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. Vertical component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. Lagrangian multiplier. Criteria of termination of velocity computing.

Computes flow for every pixel of the first input image using Lucas & Kanade algorithm

First image, 8-bit, single-channel. Second image, 8-bit, single-channel. Size of the averaging window used for grouping pixels. Horizontal component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. Vertical component of the optical flow of the same size as input images, 32-bit floating-point, single-channel.

Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids

First frame, at time t. Second frame, at time t + dt . Buffer for the pyramid for the first frame. If the pointer is not null , the buffer must have a sufficient size to store the pyramid from level 1 to level #level ; the total size of (image_width+8)*image_height/3 bytes is sufficient. Similar to prev_pyr, used for the second frame. Array of points for which the flow needs to be found. Array of 2D points containing calculated new positions of input features in the second image. Size of the search window of each pyramid level. Maximal pyramid level number. If 0 , pyramids are not used (single level), if 1 , two levels are used, etc. Array. Every element of the array is set to 1 if the flow for the corresponding feature has been found, 0 otherwise. Specifies when the iteration process of finding the flow for each point on each pyramid level should be stopped. Miscellaneous flags

Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids

First frame, at time t. Second frame, at time t + dt . Buffer for the pyramid for the first frame. If the pointer is not null , the buffer must have a sufficient size to store the pyramid from level 1 to level #level ; the total size of (image_width+8)*image_height/3 bytes is sufficient. Similar to prev_pyr, used for the second frame. Array of points for which the flow needs to be found. Array of 2D points containing calculated new positions of input features in the second image. Size of the search window of each pyramid level. Maximal pyramid level number. If 0 , pyramids are not used (single level), if 1 , two levels are used, etc. Array. Every element of the array is set to 1 if the flow for the corresponding feature has been found, 0 otherwise. Array of double numbers containing difference between patches around the original and moved points. Optional parameter; can be NULL . Specifies when the iteration process of finding the flow for each point on each pyramid level should be stopped. Miscellaneous flags

Performs Principal Component Analysis of a vector set

The input data; each vector is either a single row (CV_PCA_DATA_AS_ROW) or a single column (CV_PCA_DATA_AS_COL). The mean (average) vector, computed inside the function or provided by user. The output eigenvalues of covariation matrix. The output eigenvectors of covariation matrix (i.e. principal components); one vector per row. The operation flags

Calculates pair-wise geometrical histogram for contour

Input contour. Currently, only integer point coordinates are allowed. Calculated histogram; must be two-dimensional.

Divides one histogram by another.

first histogram (the divisor). second histogram. destination histogram.

Divides one histogram by another.

first histogram (the divisor). second histogram. destination histogram. scale factor for the destination histogram.

Calculates coordinates of Voronoi diagram cells.

Delaunay subdivision, where all the points are added already.

Finds intrinsic and extrinsic camera parameters using calibration pattern

The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. The joint matrix of corresponding image points, 2xN or Nx2, where N is the total number of points in all views. Vector containing numbers of points in each particular view, 1xM or Mx1, where M is the number of a scene views. Size of the image, used only to initialize intrinsic camera matrix. The output camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATION are specified, some or all of fx, fy, cx, cy must be initialized. The output 4x1 or 1x4 vector of distortion coefficients [k1, k2, p1, p2].

Finds intrinsic and extrinsic camera parameters using calibration pattern

The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 Image size in pixels

Finds intrinsic and extrinsic camera parameters using calibration pattern

The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 Image size in pixels Aperture width in realworld units Aperture width in realworld units

Finds intrinsic and extrinsic camera parameters using calibration pattern

The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 Image size in pixels Aperture width in realworld units Aperture width in realworld units Field of view angle in x direction in degrees Field of view angle in y direction in degrees

Finds intrinsic and extrinsic camera parameters using calibration pattern

Finds object center, size, and orientation

Back projection of object histogram (see cvCalcBackProject). Initial search window. Criteria applied to determine when the window search should be finished. The function returns number of iterations made within cvMeanShift.

Finds object center, size, and orientation

Back projection of object histogram (see cvCalcBackProject). Initial search window. Criteria applied to determine when the window search should be finished. Resultant structure that contains converged search window coordinates (comp->rect field) and sum of all pixels inside the window (comp->area field). The function returns number of iterations made within cvMeanShift.

Finds object center, size, and orientation

Back projection of object histogram (see cvCalcBackProject). Initial search window. Criteria applied to determine when the window search should be finished. Resultant structure that contains converged search window coordinates (comp->rect field) and sum of all pixels inside the window (comp->area field). Circumscribed box for the object. If not NULL, contains object size and orientation. The function returns number of iterations made within cvMeanShift.

Finds the edges on the input image image and marks them in the output image edges using the Canny algorithm. The smallest of threshold1 and threshold2 is used for edge linking, the largest - to find initial segments of strong edges.

Input image. Image to store the edges found by the function. The first threshold. The second threshold.

Input image. Image to store the edges found by the function. The first threshold. The second threshold. Aperture parameter for Sobel operator.

Calculates magnitude and/or angle of 2d vectors

The array of x-coordinates The array of y-coordinates The destination array of magnitudes, may be set to null if it is not needed

Calculates magnitude and/or angle of 2d vectors

The array of x-coordinates The array of y-coordinates The destination array of magnitudes, may be set to null if it is not needed The destination array of angles, may be set to null if it is not needed. The angles are measured in radians (0..2π) or in degrees (0..360°).

Calculates magnitude and/or angle of 2d vectors

Calculates cubic root

The input floating-point value

Returns the minimum integer value that is not smaller than the argument.

The input floating-point value

Checks every element of input array for invalid values

returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The array to check. The operation flags returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The array to check. The operation flags The inclusive lower boundary of valid values range. It is used only if CV_CHECK_RANGE is set. The exclusive upper boundary of valid values range. It is used only if CV_CHECK_RANGE is set. returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The array to check. returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The array to check. The operation flags returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

Performs a fast check if a chessboard is in the input image. This is a workaround to a problem of cvFindChessboardCorners being slow on images with no chessboard

input image chessboard size Returns 1 if a chessboard can be in this image and findChessboardCorners should be called, 0 if there is no chessboard, -1 in case of error

Tests contour convexity.

Tested contour (sequence or array of points)

Check termination criteria and transform it so that type=CriteriaType.Iteration | CriteriaType.Epsilon, and both max_iter and epsilon are valid

Termination criteria Default epsilon Default maximum number of iteration

Draws a circle

Image where the circle is drawn. X-coordinate of the center of the circle. Y-coordinate of the center of the circle. Radius of the circle. Circle color.

Draws a circle

Image where the circle is drawn. X-coordinate of the center of the circle. Y-coordinate of the center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn.

Draws a circle

Image where the circle is drawn. Center of the circle. Radius of the circle. Circle color.

Draws a circle

Image where the circle is drawn. Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn.

Draws a circle

Image where the circle is drawn. Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. Type of the circle boundary.

Draws a circle

Image where the circle is drawn. X-coordinate of the center of the circle. Y-coordinate of the center of the circle. Radius of the circle. Circle color.

Draws a circle

Image where the circle is drawn. Center of the circle. Radius of the circle. Circle color.

Draws a circle

Image where the circle is drawn. Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn.

Draws a circle

Returns index of graph vertex

Graph. The function cvClearGraph removes all vertices and edges from the graph. The function has O(1) time complexity.

Sets all histogram bins to 0 in case of dense histogram and removes all histogram bins in case of sparse array.

Histogram.

Clears memory storage

Memory storage.

Clears the particular array element

Input array. Array of the element indices

Clears sequence

Sequence.

Clears set

Cleared set. The function cvClearSet removes all elements from set. It has O(1) time complexity.

Removes all virtual points

Delaunay subdivision.

Clips the line against the image rectangle

Size of the image. First ending point of the line segment. It is modified by the function. Second ending point of the line segment. It is modified by the function. The function cvClipLine calculates a part of the line segment which is entirely in the image. It returns 0 if the line segment is completely outside the image and 1 otherwise.

Makes a clone of the object

The object to clone.

Makes a clone of the object

The object to clone.

Clone graph

Graph. Container for the copy. The function cvCloneGraph creates full copy of the graph. If the graph vertices or edges have pointers to some external data, it still be shared between the copies. The vertex and edge indices in the new graph may be different from the original, because the function defragments the vertex and edge sets.

Makes a full copy of image

Original image.

Creates matrix copy

Input matrix a copy of input array

Creates full copy of multi-dimensional array

Input array a copy of input array

Creates a copy of sequence

Sequence.

Creates a copy of sequence

Sequence. The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence.

Creates a copy of sequence

Element type Sequence.

Creates a copy of sequence

Element type Sequence. The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence.

Creates full copy of sparse array

Input array a copy of input array

Performs per-element comparison of two arrays

The first source array. The second source array. Both source array must have a single channel. The destination array, must have 8u or 8s type. The flag specifying the relation between the elements to be checked

Performs per-element comparison of array and scalar

The source array, must have a single channel. The scalar value to compare each array element with. The destination array, must have 8u or 8s type. The flag specifying the relation between the elements to be checked

Initializes sample set for ConDensation algorithm

Structure to be initialized. Vector of the lower boundary for each dimension. Vector of the upper boundary for each dimension.

Estimates subsequent model state

Structure to be updated.

Completes the symmetric matrix from the lower part

Completes the symmetric matrix from the lower (LtoR=0) or from the upper (LtoR!=0) part

Compares two dense histograms.

The first dense histogram. The second dense histogram. Comparison method.

Computes r3 = rodrigues(rodrigues(r2)*rodrigues(r1)), t3 = rodrigues(r2)*t1 + t2 and the respective derivatives

For points in one image of stereo pair computes the corresponding epilines in the other image

The input points. 2xN, Nx2, 3xN or Nx3 array (where N number of points). Multi-channel 1xN or Nx1 array is also acceptable. Index of the image (1 or 2) that contains the points Fundamental matrix Computed epilines, 3xN or Nx3 array

Calculates area of the whole contour or contour section.

Contour (sequence or array of vertices).

Calculates area of the whole contour or contour section.

Contour (sequence or array of vertices). Starting and ending points of the contour section of interest, by default area of the whole contour is calculated.

Restores contour from tree.

Contour tree. Container for the reconstructed contour. Criteria, where to stop reconstruction.

Alias for Moments with CvSeq contours

Contours Moments

Alias for cvArcLength(curve,Whole_Seq,1)

Contours

Converts one image to another and flips the result vertically if required.

Source image. Destination image. Must be single-channel or 3-channel 8-bit image. The operation flags

Converts mapx & mapy from floating-point to integer formats for cvRemap

Convert points to/from homogeneous coordinates

The input point array, 2xN, Nx2, 3xN, Nx3, 4xN or Nx4 (where N is the number of points). Multi-channel 1xN or Nx1 array is also acceptable. The output point array, must contain the same number of points as the input; The dimensionality must be the same, 1 less or 1 more than the input, and also within 2..4.

Convert points to/from homogeneous coordinates

Converts one array to another with optional linear transformation

Source array. Destination array.

Converts one array to another with optional linear transformation

Source array. Destination array. Scale factor.

Converts one array to another with optional linear transformation

Source array. Destination array. Scale factor. Value added to the scaled source array elements.

Converts one array to another with optional linear transformation

Source array. Destination array.

Converts one array to another with optional linear transformation

Source array. Destination array. Scale factor.

Converts one array to another with optional linear transformation

Source array. Destination array. Scale factor. Value added to the scaled source array elements.

Converts one array to another with optional linear transformation

Source array. Destination array.

Converts one array to another with optional linear transformation

Source array. Destination array. Scale factor.

Converts one array to another with optional linear transformation

Source array. Destination array. Scale factor. Value added to the scaled source array elements.

Converts one array to another with optional linear transformation

Source array. Destination array.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Source array. Destination array (should have 8u depth).

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Source array. Destination array (should have 8u depth). ScaleAbs factor.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Source array. Destination array (should have 8u depth). ScaleAbs factor. Value added to the scaled source array elements.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Source array. Destination array (should have 8u depth).

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Source array. Destination array (should have 8u depth). ScaleAbs factor.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Source array. Destination array (should have 8u depth). ScaleAbs factor. Value added to the scaled source array elements.

Finds convex hull of point set

Array of 2D points with 32-bit integer or floating-point coordinates. Vector of 0-based point indices of the hull points in the original array. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

Array of 2D points with 32-bit integer coordinates. Vector of 0-based point indices of the hull points in the original array. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

Array of 2D points with 32-bit floating-point coordinates. Vector of 0-based point indices of the hull points in the original array. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

Array of 2D points with 32-bit integer or floating-point coordinates. The output convex hull. It is either a vector of points that form the hull. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

Array of 2D points with 32-bit integer coordinates. The output convex hull. It is either a vector of points that form the hull. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

Array of 2D points with 32-bit floating-point coordinates. The output convex hull. It is either a vector of points that form the hull. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convexity defects of contour

Input contour. Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0. Container for output sequence of convexity defects. If it is null, contour or hull (in that order) storage is used.

Finds convexity defects of contour

Input contour. Convex hull obtained using cvConvexHull2 that should contain indices to the contour points

Copies one array to another

The source array. The destination array.

Copies one array to another

The source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

The function cvCopyHist makes a copy of the histogram. If the second histogram pointer dst is null, a new histogram of the same size as src is created. Otherwise, both histograms must have equal types and sizes. Then the function copies the source histogram bins values to destination histogram and sets the same bin values ranges as in src.

Source histogram. Reference to destination histogram.

Copies image and makes border around it.

The source image. The destination image. Coordinates of the top-left corner (or bottom-left in case of images with bottom-left origin) of the destination image rectangle where the source image (or its ROI) is copied. Size of the rectanlge matches the source image size/ROI size. Type of the border to create around the copied source image rectangle.

Copies image and makes border around it.

Calculates eigenvalues and eigenvectors of image blocks for corner detection

Input image. Image to store the results. It must be 6 times wider than the input image. Neighborhood size.

Calculates eigenvalues and eigenvectors of image blocks for corner detection

Input image. Image to store the results. It must be 6 times wider than the input image. Neighborhood size. Aperture parameter for Sobel operator

Runs the Harris edge detector on image. Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood.

Input image. Image to store the Harris detector responces. Should have the same size as image. Neighborhood size.

Input image. Image to store the Harris detector responces. Should have the same size as image. Neighborhood size. Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing.

Calculates minimal eigenvalue of gradient matrices for corner detection

Input image. Image to store the minimal eigen values. Should have the same size as image Neighborhood size.

Calculates minimal eigenvalue of gradient matrices for corner detection

Input image. Image to store the minimal eigen values. Should have the same size as image Neighborhood size. Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing.

The Optimal Triangulation Method

3x3 fundamental matrix 2xN matrix containing the first set of points 2xN matrix containing the second set of points the optimized points1_. if this is null, the corrected points are placed back in points1_ the optimized points2_. if this is null, the corrected points are placed back in points2_

Counts non-zero array elements

The array, must be single-channel array or multi-channel image with COI set. the number of non-zero elements in arr

Create a button on the control panel

Name of the button ( if null, the name will be “button <number of boutton>”)

Create a button on the control panel

Name of the button ( if null, the name will be “button <number of boutton>”) Pointer to the function to be called every time the button changed its state.

Create a button on the control panel

Name of the button ( if null, the name will be “button <number of boutton>”) Pointer to the function to be called every time the button changed its state. object passed to the callback function.

Create a button on the control panel

Name of the button ( if null, the name will be “button <number of boutton>”) Pointer to the function to be called every time the button changed its state. object passed to the callback function. button type

Create a button on the control panel

Allocates and initialized the CvCapture structure for reading a video stream from the camera. Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394).

Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed.

Device type

Creates child memory storage

Parent memory storage.

Allocates ConDensation filter structure

Dimension of the state vector. Dimension of the measurement vector. Number of samples.

Creates hierarchical representation of contour

Input contour. Container for output tree. Approximation accuracy.

Allocates array data.

Array header.

Constructs a tree of feature vectors

n x d matrix of n d-dimensional feature vectors (CV_32FC1 or CV_64FC1).

Allocates and initialized the CvCapture structure for reading the video stream from the specified file. After the allocated structure is not used any more it should be released by cvReleaseCapture function.

Name of the video file.

Creates a histogram of the specified size and returns the pointer to the created histogram.

Number of histogram dimensions. Histogram representation format.

Creates a histogram of the specified size and returns the pointer to the created histogram.

Number of histogram dimensions. Histogram representation format. Array of ranges for histogram bins. Its meaning depends on the uniform parameter value. The ranges are used for when histogram is calculated or backprojected to determine, which histogram bin corresponds to which value/tuple of values from the input image[s].

Creates a histogram of the specified size and returns the pointer to the created histogram.

Creates empty graph

Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) The graph container. The function cvCreateGraph creates an empty graph and returns it.

Creates empty graph

Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. Graph header size; may not be less than sizeof(CvGraph). Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) The graph container. The function cvCreateGraph creates an empty graph and returns it.

Creates structure for depth-first graph traversal

Graph.

Creates structure for depth-first graph traversal

Graph. Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices).

Creates structure for depth-first graph traversal

Graph. Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices). Event mask indicating which events are interesting to the user (where cvNextGraphItem function returns control to the user) It can be CV_GRAPH_ALL_ITEMS (all events are interesting) or combination of the following flags:
* CV_GRAPH_VERTEX - stop at the graph vertices visited for the first time
* CV_GRAPH_TREE_EDGE - stop at tree edges (tree edge is the edge connecting the last visited vertex and the vertex to be visited next)
* CV_GRAPH_BACK_EDGE - stop at back edges (back edge is an edge connecting the last visited vertex with some of its ancestors in the search tree)
* CV_GRAPH_FORWARD_EDGE - stop at forward edges (forward edge is an edge conecting the last visited vertex with some of its descendants in the search tree). The forward edges are only possible during oriented graph traversal)
* CV_GRAPH_CROSS_EDGE - stop at cross edges (cross edge is an edge connecting different search trees or branches of the same tree. The cross edges are only possible during oriented graphs traversal)
* CV_GRAPH_ANY_EDGE - stop and any edge (tree, back, forward and cross edges)
* CV_GRAPH_NEW_TREE - stop in the beginning of every new search tree. When the traversal procedure visits all vertices and edges reachible from the initial vertex (the visited vertices together with tree edges make up a tree), it searches for some unvisited vertex in the graph and resumes the traversal process from that vertex. Before starting a new tree (including the very first tree when cvNextGraphItem is called for the first time) it generates CV_GRAPH_NEW_TREE event.
For unoriented graphs each search tree corresponds to a connected component of the graph.
* CV_GRAPH_BACKTRACKING - stop at every already visited vertex during backtracking - returning to already visited vertexes of the traversal tree.

Creates header and allocates data

Image width and height. Bit depth of image elements. Number of channels per element(pixel). Reference to image header

Allocates, initializes, and returns structure IplImage

Image width and height. Image depth. Number of channels. Reference to image header

Allocates Kalman filter structure

dimensionality of the state vector dimensionality of the measurement vector Kalman structure

Allocates Kalman filter structure

dimensionality of the state vector dimensionality of the measurement vector dimensionality of the control vector

Constructs kd-tree from set of feature descriptors

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions.

(not supported argument on OpenCvSharp)

Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix.

Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements.

allocates new matrix header and returns pointer to it. The matrix data can further be allocated using cvCreateData or set explicitly to user-allocated data via cvSetData.

Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements.

Allocates header for multi-dimensional dense array and the underlying data, and returns pointer to the created array.

Number of array dimensions. It must not exceed CV_MAX_DIM (=32 by default, though it may be changed at build time) Array of dimension sizes. Type of array elements.

Allocates header for multi-dimensional dense array. The array data can further be allocated using cvCreateData or set explicitly to user-allocated data via cvSetData.

Number of array dimensions. Array of dimension sizes. Type of array elements.

Construct in-memory LSH table, with n bins.

Creates memory storage

Size of the storage blocks in bytes. If it is 0, the block size is set to default value - currently it is ≈64K.

Initializes structure containing object information

Array of points of the 3D object model.

Initializes structure containing object information

Array of points of the 3D object model. Number of object points.

Builds pyramid for an image

Constructs spill-tree from set of feature descriptors

Creates sequence

Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. Size of the sequence header; must be greater or equal to sizeof(CvSeq). If a specific type or its extension is indicated, this type must fit the base type header. Size of the sequence elements in bytes. The size must be consistent with the sequence type. For example, for a sequence of points to be created, the element type CV_SEQ_ELTYPE_POINT should be specified and the parameter elemSize must be equal to sizeof(CvPoint). Sequence location.

Creates sequence

Element type (ex. int, CvPoint) Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. Size of the sequence header; must be greater or equal to sizeof(CvSeq). If a specific type or its extension is indicated, this type must fit the base type header. Sequence location.

Creates empty set

Type of the created set. Set header size; may not be less than sizeof(CvSet). Set element size; may not be less than CvSetElem. Container for the set.

Creates sparse array

Number of array dimensions. As opposite to the dense matrix, the number of dimensions is practically unlimited (up to 2^16). Array of dimension sizes. Type of array elements.

Creates block matching stereo correspondence structure

stereo correspondence structure

Creates block matching stereo correspondence structure

ID of one of the pre-defined parameter sets. Any of the parameters can be overridden after creating the structure. stereo correspondence structure

Creates block matching stereo correspondence structure

ID of one of the pre-defined parameter sets. Any of the parameters can be overridden after creating the structure. The number of disparities. If the parameter is 0, it is taken from the preset, otherwise the supplied value overrides the one from preset. stereo correspondence structure

Creates the state of graph cut-based stereo correspondence algorithm

The number of disparities. The disparity search range will be state->minDisparity ≤ disparity < state->minDisparity + state->numberOfDisparities Maximum number of iterations. On each iteration all possible (or reasonable) alpha-expansions are tried. The algorithm may terminate earlier if it could not find an alpha-expansion that decreases the overall cost function value. stereo correspondence structure

Allocates and fills the structure IplConvKernel, which can be used as a structuring element in the morphological operations.

Number of columns in the structuring element. Number of rows in the structuring element. Relative horizontal offset of the anchor point. Relative vertical offset of the anchor point. Shape of the structuring element. Pointer to the structuring element data, a plane array, representing row-by-row scanning of the element matrix. Non-zero values indicate points that belong to the element. If the pointer is null, then all values are considered non-zero, that is, the element is of a rectangular shape. This parameter is considered only if the shape is CV_SHAPE_CUSTOM .

Creates empty Delaunay triangulation. The users must initialize the returned value by cvInitSubdivDelaunay2D.

Creates empty Delaunay triangulation

Rectangle that includes all the 2d points that are to be added to subdivision. Container for subdivision.

Creates the trackbar (a.k.a. slider or range control) with the specified name and range, assigns the variable to be syncronized with trackbar position and specifies callback function to be called on trackbar position change. The created trackbar is displayed on top of given window.

Name of created trackbar. Name of the window which will e used as a parent for created trackbar. Ref of int value Maximal position of the slider. Minimal position is always 0. Reference to the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int);Can be null if callback is not required.

Name of created trackbar. Name of the window which will e used as a parent for created trackbar. Initial position of the slider. Maximal position of the slider. Minimal position is always 0. Reference to the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int);Can be null if callback is not required.

Creates video writer structure.

Name of the output video file. 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. Framerate of the created video stream. Size of video frames. If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only).

Calculates cross product of two 3D vectors

The first source vector. The second source vector. The destination vector.

Converts image from one color space to another.

The source 8-bit (8u), 16-bit (16u) or single-precision floating-point (32f) image. The destination image of the same data type as the source one. The number of channels may be different. Color conversion operation that can be specifed using CV_<src_color_space>2<dst_color_space> constants (see below).

Copies sequence to one continuous block of memory

Sequence. destination array that must be large enough. It should be a pointer to data, not a matrix header.

Copies sequence to one continuous block of memory

Sequence. destination array that must be large enough. It should be a pointer to data, not a matrix header. The sequence part to copy to the array.

Calculates angle of 2D vector

y-coordinate of 2D vector x-coordinate of 2D vector

Fills convex polygon

Image. Array of pointers to a single polygon. Polygon color.

Fills convex polygon

Image. Array of pointers to a single polygon. Polygon color. Type of the polygon boundaries.

Fills convex polygon

Image. Array of pointers to a single polygon. Polygon color. Type of the polygon boundaries. Number of fractional bits in the vertex coordinates.

Fills polygons interior

Image. Array of pointers to polygons. Polygon color.

Fills polygons interior

Image. Array of pointers to polygons. Polygon color. ype of the polygon boundaries.

Fills polygons interior

Image. Array of pointers to polygons. Polygon color. ype of the polygon boundaries. Number of fractional bits in the vertex coordinates.

Applies arbitrary linear filter to the image. In-place operation is supported. When the aperture is partially outside the image, the function interpolates outlier pixel values from the nearest pixels that is inside the image.

The source image. The destination image. Convolution kernel, single-channel floating point matrix. If you want to apply different kernels to different channels, split the image using cvSplit into separate color planes and process them individually. The anchor of the kernel that indicates the relative position of a filtered point within the kernel. The anchor shoud lie within the kernel. The special default value (-1,-1) means that it is at the kernel center.

Finds positions of internal corners of the chessboard

Source chessboard view; it must be 8-bit grayscale or color image. The number of inner corners per chessboard row and column. The output array of corners detected. returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false.

Finds positions of internal corners of the chessboard

Source chessboard view; it must be 8-bit grayscale or color image. The number of inner corners per chessboard row and column. The output array of corners detected. The output corner counter. If it is not null, the function stores there the number of corners found. returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false.

Finds positions of internal corners of the chessboard

Source chessboard view; it must be 8-bit grayscale or color image. The number of inner corners per chessboard row and column. The output array of corners detected. The output corner counter. If it is not null, the function stores there the number of corners found. Various operation flags returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false.

Retrieves contours from the binary image and returns the number of retrieved contours.

The source 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - that is image treated as binary. To get such a binary image from grayscale, one may use cvThreshold, cvAdaptiveThreshold or cvCanny. The function modifies the source image content. Container of the retrieved contours. Output parameter, will contain the pointer to the first outer contour. Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. The number of retrieved contours.

Retrieves contours from the binary image and returns the number of retrieved contours.

Iterates to find the sub-pixel accurate location of corners, or radial saddle points.

Input image. Initial coordinates of the input corners and refined coordinates on output. Number of corners. Half sizes of the search window. Half size of the dead region in the middle of the search zone over which the summation in formulae below is not done. It is used sometimes to avoid possible singularities of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such size. Criteria for termination of the iterative process of corner refinement. That is, the process of corner position refinement stops either after certain number of iteration or when a required accuracy is achieved. The criteria may specify either of or both the maximum number of iteration and the required accuracy.

Finds high-curvature points of the contour

pointer to input contour object. memory storage for IPAN algorithm - minimal distance for IPAN algorithm - maximal distance for IPAN algorithm - neighborhood distance (must be not greater than dmaximal distance) for IPAN algorithm - maximal possible angle of curvature array of dominant points indices

Finds extrinsic camera parameters for particular view

The array of object points, 3xN or Nx3, where N is the number of points in the view. The array of corresponding image points, 2xN or Nx2, where N is the number of points in the view. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is null, all distortion coefficients are considered 0's. The output 3x1 or 1x3 rotation vector (compact representation of a rotation matrix, see cvRodrigues2). The output 3x1 or 1x3 translation vector.

Finds extrinsic camera parameters for particular view

The array of object points, 3xN or Nx3, where N is the number of points in the view. The array of corresponding image points, 2xN or Nx2, where N is the number of points in the view. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is NULL, all distortion coefficients are considered 0's. The output 3x1 or 1x3 rotation vector (compact representation of a rotation matrix, see cvRodrigues2). The output 3x1 or 1x3 translation vector.

Finds approximate k nearest neighbors of given vectors using best-bin-first search.

pointer to kd-tree index of reference vectors. m x d matrix of (row-)vectors to find the nearest neighbors of. m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. m x k matrix of distances to k nearest neighbors.

Finds approximate k nearest neighbors of given vectors using best-bin-first search.

Performs orthogonal range seaching on the given kd-tree.

Pointer to kd-tree index of reference vectors. 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving minimum value for each dimension. 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving maximum value for each dimension. 1 x m or m x 1 vector (CV_32SC1) to contain output row indices (referring to matrix passed to cvCreateFeatureTree). the number of such vectors found.

Calculates fundamental matrix from corresponding points in two images

Array of the first image points of 2xN, Nx2, 3xN or Nx3 size (where N is number of points). Multi-channel 1xN or Nx1 array is also acceptable. The point coordinates should be floating-point (single or double precision) Array of the second image points of the same size and format as points1 The output fundamental matrix or matrices. The size should be 3x3 or 9x3 (7-point method may return up to 3 matrices). Method for computing the fundamental matrix The parameter is used for RANSAC method only. It is the maximum distance from point to epipolar line in pixels, beyond which the point is considered an outlier and is not used for computing the final fundamental matrix. Usually it is set somewhere from 1 to 3. The parameter is used for RANSAC or LMedS methods only. It denotes the desirable level of confidence of the fundamental matrix estimate.

Calculates fundamental matrix from corresponding points in two images

Finds edge in graph

Graph. Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists.

Finds edge in graph

Graph. Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists.

Finds edge in graph

Finds perspective transformation between two planes

Point coordinates in the original plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates), where N is the number of points. Point coordinates in the destination plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates) Output 3x3 homography matrix.

Finds perspective transformation between two planes

Finds the closest subdivision vertex to given point

Delaunay or another subdivision. Input point.

Finds next contour in the image

Contour scanner initialized by The function cvStartFindContours

Calculates disparity for stereo-pair

Left image of stereo pair, rectified grayscale 8-bit image Right image of stereo pair, rectified grayscale 8-bit image Algorithm used to find a disparity (now only CV_DISPARITY_BIRCHFIELD is supported) Destination depth image, grayscale 8-bit image that codes the scaled disparity, so that the zero disparity (corresponding to the points that are very far from the cameras) maps to 0, maximum disparity maps to 255. Maximum possible disparity. The closer the objects to the cameras, the larger value should be specified here. Too big values slow down the process significantly. Constant occlusion penalty, default=25 Constant match reward, default=5 Defines a highly reliable region (set of contiguous pixels whose reliability is at least param3), default=12 Defines a moderately reliable region, default=15 Defines a slightly reliable region, default=25

Computes the disparity map using block matching algorithm

The left single-channel, 8-bit image. The right image of the same size and the same type. The output single-channel 16-bit signed disparity map of the same size as input images. Its elements will be the computed disparities, multiplied by 16 and rounded to integer's. Stereo correspondence structure.

Computes the disparity map using graph cut-based algorithm

The left single-channel, 8-bit image. The right image of the same size and the same type. The optional output single-channel 16-bit signed left disparity map of the same size as input images. The optional output single-channel 16-bit signed right disparity map of the same size as input images. Stereo correspondence structure. If the parameter is not zero, the algorithm will start with pre-defined disparity maps. Both dispLeft and dispRight should be valid disparity maps. Otherwise, the function starts with blank disparity maps (all pixels are marked as occlusions).

Finds type by its name

Type name.

Returns the beginning of type list

the first type of the list of registered types.

Fits ellipse to set of 2D points

Array or sequence of the points. ellipse that fits best (in least-squares sense) to a set of 2D points.

Fits ellipse to set of 2D points

Array of the points. ellipse that fits best (in least-squares sense) to a set of 2D points.

Fits line to 2D or 3D point set

Sequence or array of 2D or 3D points with 32-bit integer or floating-point coordinates. The distance used for fitting (see the discussion). Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. The output line parameters. In case of 2d fitting it is array of 4 floats (vx, vy, x0, y0) where (vx, vy) is a normalized vector collinear to the line and (x0, y0) is some point on the line. In case of 3D fitting it is array of 6 floats (vx, vy, vz, x0, y0, z0) where (vx, vy, vz) is a normalized vector collinear to the line and (x0, y0, z0) is some point on the line.

Fits line to 2D point set

Sequence or array of 2D points with 32-bit integer coordinates. The distance used for fitting (see the discussion). Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. The output line parameters. (vx, vy) is a normalized vector collinear to the line and (x0, y0) is some point on the line.

Fits line to 2D point set

Sequence or array of 2D points with floating-point coordinates. The distance used for fitting (see the discussion). Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. The output line parameters. (vx, vy) is a normalized vector collinear to the line and (x0, y0) is some point on the line.

Fits line to 3D point set

Sequence or array of 3D points with floating-point coordinates. The distance used for fitting (see the discussion). Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. The output line parameters. (vx, vy, vz) is a normalized vector collinear to the line and (x0, y0, z0) is some point on the line.

Flip a 2D array around vertical, horizontal or both axises

Source array.

Flip a 2D array around vertical, horizontal or both axises

Source array. Destination array. If dst = null the flipping is done in-place.

Flip a 2D array around vertical, horizontal or both axises

Source array. Destination array. If dst = null the flipping is done in-place. Specifies how to flip the array.

Flip a 2D array around vertical, horizontal or both axises

Source array.

Flip a 2D array around vertical, horizontal or both axises

Source array. Destination array. If dst = null the flipping is done in-place.

Flip a 2D array around vertical, horizontal or both axises

Source array. Destination array. If dst = null the flipping is done in-place. Specifies how to flip the array.

Fills a connected component with given color.

Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. The starting point. New value of repainted domain pixels.

Fills a connected component with given color.

Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. The starting point. New value of repainted domain pixels. Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. Pointer to structure the function fills with the information about the repainted domain.

Fills a connected component with given color.

Returns the maximum integer value that is not larger than the argument.

The input floating-point value

Updates sequence headers from the writer state

Writer state

Create the font to be used to draw text on an image

Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used.

Create the font to be used to draw text on an image

Deallocates memory buffer

Double pointer to released buffer.

Performs generalized matrix multiplication

The first source array. The second source array. Scale factor The third source array (shift). Can be null, if there is no shift. Scale factor The destination array.

Performs generalized matrix multiplication

The first source array. The second source array. Scale factor The third source array (shift). Can be null, if there is no shift. Scale factor The destination array. The operation flags

Performs generalized matrix multiplication

The first source array. The second source array. The destination array.

Performs generalized matrix multiplication

The first source array. The second source array. The third source array (shift). Can be null, if there is no shift. The destination array.

Performs generalized matrix multiplication

The first source array. The second source array. Scale factor The third source array (shift). Can be null, if there is no shift. Scale factor The destination array.

Performs generalized matrix multiplication

The first source array. The second source array. Scale factor The third source array (shift). Can be null, if there is no shift. Scale factor The destination array. The operation flags

Return the particular array element

Input array. The first zero-based component of the element index

Return the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index

Return the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index

Return the particular array element

Input array. Array of the element indices the particular array element

Calculates affine transform from 3 corresponding points.

Coordinates of 3 triangle vertices in the source image. Coordinates of the 3 corresponding triangle vertices in the destination image.

Calculates affine transform from 3 corresponding points.

Coordinates of 3 triangle vertices in the source image. Coordinates of the 3 corresponding triangle vertices in the destination image. Pointer to the destination 2×3 matrix.

Retrieves the specified property of camera or video file.

video capturing structure. property identifier. property value

Retrieves the specified property of camera or video file.

video capturing structure. property identifier. property value

Retrieves central moment from moment state structure

Moment state structure x order of the retrieved moment, x_order >= 0 y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 Central moment

Returns array column

Input array. Reference to the resulting sub-array header. Zero-based index of the selected column.

Returns array column span

Input array. Reference to the resulting sub-array header. Zero-based index of the starting column (inclusive) of the span. Zero-based index of the ending column (exclusive) of the span.

Returns one of array diagonals

Input array. Reference to the resulting sub-array header.

Returns one of array diagonals

Input array. Reference to the resulting sub-array header. Array diagonal. Zero corresponds to the main diagonal, -1 corresponds to the diagonal above the main etc., 1 corresponds to the diagonal below the main etc.

Return number of array dimensions and their sizes

Input array. number of array dimensions.

Return number of array dimensions and their sizes

Input array. Optional output vector of the array dimension sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next. number of array dimensions.

Return the size of particular dimension

Input array. Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width). the particular dimension size (number of elements per that dimension).

Returns type of array elements

Input array. type of the array elements

Returns the current error mode

the current error mode

Returns the current error status

the current error status

Finds node in the map or file storage

File storage. The parent map. If it is null, the function searches a top-level node. If both map and key are nulls, the function returns the root file node - a map that contains top-level nodes. Unique pointer to the node name, retrieved with cvGetHashedKey.

Finds node in the map or file storage

Returns name of file node

File node. name of the file node or null

Finds node in the map or file storage

File storage. The parent map. If it is null, the function searches in all the top-level nodes (streams), starting from the first one. The file node name.

Finds graph vertex by index

Graph. Index of the vertex. The function cvGetGraphVtx finds the graph vertex by index and returns the pointer to it or null if the vertex does not belong to the graph.

Returns a unique pointer for given name

File storage. Literal node name. The unique pointer for each particular file node name.

Returns a unique pointer for given name

File storage. Literal node name. Length of the name (if it is known a priori), or -1 if it needs to be calculated. The unique pointer for each particular file node name.

Returns pointer to histogram bin.

Histogram. 1st index of the bin.

Returns pointer to histogram bin.

Histogram. 1st index of the bin. 2rd index of the bin.

Returns pointer to histogram bin.

Histogram. 1st index of the bin. 2nd index of the bin. 3rd index of the bin.

Returns pointer to histogram bin.

Histogram. Indices of the bin.

Calculates seven Hu invariants

Moment state structure Pointer to Hu moments structure

Returns image header for arbitrary array

Input array. returns the image header for the input array that can be a matrix

Returns image header for arbitrary array

Input array. IplImage structure used as a temporary buffer. returns the image header for the input array that can be a matrix

Returns index of channel of interest

Image header. channel of interest of the image (it returns 0 if all the channels are selected)

Returns image ROI coordinates. The rectangle cvRect(0,0,image.Width,image.Height) is returned if there is no ROI.

Image header.

Returns matrix header for arbitrary array

Input array. returns a matrix header for the input array that can be a matrix

Returns matrix header for arbitrary array

Input array. Pointer to CvMat structure used as a temporary buffer. returns a matrix header for the input array that can be a matrix

Returns matrix header for arbitrary array

Input array. Pointer to CvMat structure used as a temporary buffer. Optional output parameter for storing COI. returns a matrix header for the input array that can be a matrix

Returns matrix header for arbitrary array

Input array. Pointer to CvMat structure used as a temporary buffer. Optional output parameter for storing COI. If true, the function accepts multi-dimensional dense arrays (CvMatND*) and returns 2D (if CvMatND has two dimensions) or 1D matrix (when CvMatND has 1 dimension or more than 2 dimensions). The array must be continuous. returns a matrix header for the input array that can be a matrix

Moves iterator to the next sparse matrix element and returns pointer to it.

Sparse array iterator.

Finds minimum and maximum histogram bins.

Histogram. The minimum value of the histogram. The maximum value of the histogram.

Finds minimum and maximum histogram bins.

Histogram. The minimum value of the histogram. The maximum value of the histogram. The array of coordinates for minimum. The array of coordinates for maximum.

Retrieves information about the registered module(s) and plugins

Name of the module of interest, or null, which means all the modules. The output parameter. Information about the module(s), including version. The list of names and versions of the optimized plugins that CXCORE was able to find and load.

Retrieves normalized central moment from moment state structure

Moment state structure x order of the retrieved moment, x_order >= 0 y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 Central moment

Returns the current number of threads that are used by parallelized (via OpenMP) OpenCV functions.

the current number of threads used

Returns optimal DFT size for given vector size

Vector size. optimal DFT size for given vector size

Returns the new camera matrix based on the free scaling parameter

The input camera matrix The input 4x1, 1x4, 5x1 or 1x5 vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3]) The original image size The free scaling parameter between 0 (when all the pixels in the undistorted image will be valid) and 1 (when all the source image pixels will be retained in the undistorted image); The output new camera matrix. The image size after rectification. By default it will be set to imageSize .

Returns the new camera matrix based on the free scaling parameter

Calculates perspective transform from 4 corresponding points.

Coordinates of 4 quadrangle vertices in the source image. Coordinates of the 4 corresponding quadrangle vertices in the destination image.

Calculates perspective transform from 4 corresponding points.

Coordinates of 4 quadrangle vertices in the source image. Coordinates of the 4 corresponding quadrangle vertices in the destination image. Pointer to the destination 3×3 matrix.

Calculates perspective transform from 4 corresponding points.

Coordinates of 4 quadrangle vertices in the source image. Coordinates of the 4 corresponding quadrangle vertices in the destination image.

Calculates perspective transform from 4 corresponding points.

Coordinates of 4 quadrangle vertices in the source image. Coordinates of the 4 corresponding quadrangle vertices in the destination image. Pointer to the destination 3×3 matrix.

Retrieves pixel quadrangle from image with sub-pixel accuracy.

Source image. Extracted quadrangle. The transformation 2 × 3 matrix [A|b].

Retrieves low-level information about the array

Array header. Output pointer to the whole image origin or ROI origin if ROI is set.

Retrieves low-level information about the array

Array header. Output pointer to the whole image origin or ROI origin if ROI is set. Output full row length in bytes.

Retrieves low-level information about the array

Array header. Output pointer to the whole image origin or ROI origin if ROI is set. Output full row length in bytes. Output ROI size.

Return the particular element of single-channel array

Input array. Must have a single channel. The first zero-based component of the element index the particular element of single-channel array.

Return the particular element of single-channel array

Input array. Must have a single channel. The first zero-based component of the element index The second zero-based component of the element index the particular element of single-channel array.

Return the particular element of single-channel array

Input array. Must have a single channel. The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index the particular element of single-channel array.

Return the particular element of single-channel array

Input array. Must have a single channel. Array of the element indices the particular element of single-channel array.

Retrieves pixel rectangle from image with sub-pixel accuracy.

Source image. Extracted rectangle. Floating point coordinates of the extracted rectangle center within the source image. The center must be inside the image.

Retrieves one of top-level nodes of the file storage

File storage. One of top-level file nodes

Retrieves one of top-level nodes of the file storage

File storage. Zero-based index of the stream. In most cases, there is only one stream in the file, however there can be several. One of top-level file nodes

Calculates affine matrix of 2d rotation.

Center of the rotation in the source image. The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). Isotropic scale factor.

Calculates affine matrix of 2d rotation.

Center of the rotation in the source image. The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). Isotropic scale factor.

Calculates affine matrix of 2d rotation.

Center of the rotation in the source image. The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). Isotropic scale factor. Pointer to the destination 2×3 matrix. The transformation maps the rotation center to itself. If this is not the purpose, the shift should be adjusted.

Returns array row

Input array. Reference to the resulting sub-array header. Zero-based index of the selected row.

Returns array row span

Input array. Reference to the resulting sub-array header. Zero-based index of the starting row (inclusive) of the span. Zero-based index of the ending row (exclusive) of the span.

Returns array row span

Input array. Reference to the resulting sub-array header. Zero-based index of the starting row (inclusive) of the span. Zero-based index of the ending row (exclusive) of the span. Index step in the row span. That is, the function extracts every delta_row-th row from start_row and up to (but not including) end_row.

Returns pointer to sequence element by its index

Element type Sequence. Index of element.

Returns pointer to sequence element by its index

Element type Sequence. Index of element.

Returns the current reader position

Reader state. the current reader position

Finds set element by its index

Set. Index of the set element within a sequence. the pointer to it or null if the index is invalid or the corresponding node is free.

Returns size of matrix or image ROI

array header.

Retrieves spatial moment from moment state structure

The moment state, calculated by cvMoments x order of the retrieved moment, x_order >= 0 y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 Spatial moments

Retrieves keypoints using the StarDetector algorithm.

The input 8-bit grayscale image Memory storage where the keypoints will be stored

Retrieves keypoints using the StarDetector algorithm.

The input 8-bit grayscale image Memory storage where the keypoints will be stored Various algorithm parameters given to the structure CvStarDetectorParams

Returns matrix header corresponding to the rectangular sub-array of input image or matrix

Input array. Reference to the resultant sub-array header. Zero-based coordinates of the rectangle of interest. Reference to the header, corresponding to a specified rectangle of the input array.

Returns matrix header corresponding to the rectangular sub-array of input image or matrix

Input array. Reference to the resultant sub-array header. Zero-based coordinates of the rectangle of interest. Reference to the header, corresponding to a specified rectangle of the input array.

Retrieves width and height of text string

Input string. Reference to the font structure. Resultant size of the text string. Height of the text does not include the height of character parts that are below the baseline. y-coordinate of the baseline relatively to the bottom-most text point.

Returns number of tics starting from some platform-dependent event (number of CPU ticks from the startup, number of milliseconds from 1970th year etc.).

Number of tics

Returns number of tics per microsecond

number of tics per microsecond.

Returns index of the current thread

Returns the current position of the specified trackbar.

Name of trackbar. Name of the window which is the parent of trackbar. the current position of the specified trackbar.

Returns native window handle (HWND in case of Win32 and GtkWidget in case of GTK+).

Name of the window. HWND in case of Win32 and GtkWidget in case of GTK+

Returns the name of window given its native handle (HWND in case of Win32 and GtkWidget in case of GTK+).

Handle of the window. Window name

Get Property of the window

Window name Property identifier Value of the specified property

Determines strong corners on image

The source 8-bit or floating-point 32-bit, single-channel image. Temporary floating-point 32-bit image of the same size as image. Another temporary image of the same size and same format as eig_image. Output parameter. Detected corners. Output parameter. Number of detected corners. Multiplier for the maxmin eigenvalue; specifies minimal accepted quality of image corners. Limit, specifying minimum possible distance between returned corners; Euclidian distance is used. Region of interest. The function selects points either in the specified region or in the whole image if the mask is null. Size of the averaging block, passed to underlying cvCornerMinEigenVal or cvCornerHarris used by the function.

Determines strong corners on image

Grabs the frame from camera or file. The grabbed frame is stored internally. The purpose of this function is to grab frame fast that is important for syncronization in case of reading from several cameras simultaneously. The grabbed frames are not exposed because they may be stored in compressed format (as defined by camera/driver). To retrieve the grabbed frame, cvRetrieveFrame should be used.

video capturing structure.

Adds vertex to graph

Graph. The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index.

Adds vertex to graph

Graph. Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index.

Adds vertex to graph

Graph. Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). The address of the new vertex is written there. The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index.

Adds edge to graph

Graph. Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Graph. Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Graph. Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. Optional output parameter to contain the address of the inserted edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Graph. Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Graph. Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Graph. Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. Optional output parameter to contain the address of the inserted edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Returns index of graph edge

Graph. Graph edge. The function cvGraphEdgeIdx returns index of the graph edge.

Returns count of edges

Graph.

Returns count of vertex

Graph.

Removes edge from graph

Graph. Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphRemoveEdge removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing.

Removes edge from graph

Graph. Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphRemoveEdgeByPtr removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing.

Removes vertex from graph

Graph. Index of the removed vertex. The function cvGraphRemoveAddVtx removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the input vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph.

Removes vertex from graph

Graph. Vertex to remove The function cvGraphRemoveVtxByPtr removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph.

Counts edges indicent to the vertex

Graph. Index of the graph vertex. The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming.

Counts edges indicent to the vertex

Graph. Index of the graph vertex. The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming.

Returns index of graph vertex

Graph. Graph vertex. The function cvGraphVtxIdx returns index of the graph vertex.

Calculates all of the decomposition coefficients for an input object. (ioFlags = CV_EIGOBJ_NO_CALLBACK)

Input object. Pointer to the array of IplImage input objects. Averaged object. Calculated coefficients; an output parameter.

Calculates all of the decomposition coefficients for an input object.

Input object. Number of eigen objects. ointer to the read callback function. Input/output flags. Pointer to the structure that contains all of the necessary data for the callback functions. Averaged object. Calculated coefficients; an output parameter.

Calculates the object projection into the eigen sub-space. (ioFlags = CV_EIGOBJ_NO_CALLBACK)

Pointer to an array of IplImage input objects. Number of eigenvectors. Previously calculated decomposition coefficients. Average vector Projection to the eigen sub-space.

Calculates the object projection into the eigen sub-space.

Pointer to to a callback function, depending on io_flags. Number of eigenvectors. Input/output flags Pointer to the structure that contains all of the necessary data for the callback functions. Previously calculated decomposition coefficients. Average vector Projection to the eigen sub-space.

Computes eigenvalues and eigenvectors of symmetric matrix

The input symmetric square matrix. It is modified during the processing. The output matrix of eigenvectors, stored as a subsequent rows. The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). Accuracy of diagonalization (typically, DBL_EPSILON=≈10-15 is enough).

Computes eigenvalues and eigenvectors of symmetric matrix

Draws simple or thick elliptic arc or fills ellipse sector

Image. Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color.

Draws simple or thick elliptic arc or fills ellipse sector

Image. Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color. Thickness of the ellipse arc.

Draws simple or thick elliptic arc or fills ellipse sector

Image. Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color. Thickness of the ellipse arc. Type of the ellipse boundary.

Draws simple or thick elliptic arc or fills ellipse sector

Image. Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color.

Draws simple or thick elliptic arc or fills ellipse sector

Image. Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color. Thickness of the ellipse arc.

Draws simple or thick elliptic arc or fills ellipse sector

Image. The enclosing box of the ellipse drawn Ellipse color.

Draws simple or thick elliptic arc or fills ellipse sector

Image. The enclosing box of the ellipse drawn Ellipse color. Thickness of the ellipse boundary.

Draws simple or thick elliptic arc or fills ellipse sector

Image. The enclosing box of the ellipse drawn Ellipse color. Thickness of the ellipse boundary. Type of the ellipse boundary

Draws simple or thick elliptic arc or fills ellipse sector

Image. The enclosing box of the ellipse drawn Ellipse color. Thickness of the ellipse boundary. Type of the ellipse boundary Number of fractional bits in the box vertex coordinates.

Approximates elliptic arc with polyline

Center of the arc. Half-sizes of the arc. See cvEllipse. Rotation angle of the ellipse in degrees. See cvEllipse. Starting angle of the elliptic arc. Ending angle of the elliptic arc. The array of points, filled by the function. Angle between the subsequent polyline vertices, approximation accuracy. So, the total number of output points will ceil((end_angle - start_angle)/delta) + 1 at max. The function cvEllipse2Poly computes vertices of the polyline that approximates the specified elliptic arc. It is used by cvEllipse. It returns the numbers of output points.

Encode image and store the result as a byte vector (single-row 8uC1 matrix)

The file extension that defines the output format The image to be written The format-specific parameters

Encode image and store the result as a byte vector (single-row 8uC1 matrix)

The file extension that defines the output format The image to be written The format-specific parameters

Finishes scanning process

Contour scanner.

Finishes process of writing sequence

Writer state the pointer to the written sequence.

Ends writing a structure

File storage.

Equalizes histogram of grayscale image.

The input 8-bit single-channel image. The output image of the same size and the same data type as src.

Erodes image by using arbitrary structuring element.

Source image. Destination image.

Erodes image by using arbitrary structuring element.

Source image. Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used.

Erodes image by using arbitrary structuring element.

Source image. Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. Number of times erosion is applied.

Raises an error

The error status. Name of the function where the error occurred. Additional information/diagnostics about the error. Name of the file where the error occurred. Line number, where the error occurred.

Returns textual description of error status code

The error status. The textual description for the specified error status code.

Estimate rigid transformation between 2 images or 2 point sets

Calculates exponent of every array element

The source array. The destination array, it should have double type or the same type as the source.

Extracts the contours of Maximally Stable Extremal Regions

Extracts Speeded Up Robust Features from image

The input 8-bit grayscale image. The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. Memory storage where keypoints and descriptors will be stored. Various algorithm parameters put to the structure CvSURFParams

Extracts Speeded Up Robust Features from image

The input 8-bit grayscale image. The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. Various algorithm parameters put to the structure CvSURFParams

Extracts Speeded Up Robust Features from image

The input 8-bit grayscale image. The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. Various algorithm parameters put to the structure CvSURFParams If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint).

Increments array data reference counter

Array header. The function cvIncRefData increments CvMat or CvMatND data reference counter and returns the new counter value if the reference counter pointer is not NULL, otherwise it returns zero.

Initializes font structure

font structure initialized by the function. Font name identifier. Only a subset of Hershey fonts are supported now. Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters.

Initializes font structure

Initializes allocated by user image header

Image header to initialise. Image width and height. Image depth. Number of channels. Initialzed IplImage header

Initializes allocated by user image header

Image header to initialise. Image width and height. Image depth. Number of channels. Origin of image Initialzed IplImage header

Initializes allocated by user image header

Image header to initialise. Image width and height. Image depth. Number of channels. Origin of image Alignment for image rows, typically 4 or 8 bytes. Initialzed IplImage header

Finds the initial camera matrix from the 3D-2D point correspondences

The joint array of object points The joint array of object point projections The array of point counts The image size in pixels The output camera matrix

Finds the initial camera matrix from the 3D-2D point correspondences

The joint array of object points The joint array of object point projections The array of point counts The image size in pixels The output camera matrix If it is zero or negative, both f_x and f_y are estimated independently. Otherwise f_x = f_y * aspectRatio

Initializes line iterator

Image to sample the line from. First ending point of the line segment. Second ending point of the line segment. Line iterator state structure to be generated. The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm.

Initializes line iterator

Image to sample the line from. First ending point of the line segment. Second ending point of the line segment. Line iterator state structure to be generated. The scanned line connectivity, 4 or 8. The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm.

Initializes line iterator

Image to sample the line from. First ending point of the line segment. Second ending point of the line segment. Line iterator state structure to be generated. The scanned line connectivity, 4 or 8. The flag, indicating whether the line should be always scanned from the left-most point to the right-most out of pt1 and pt2 (left_to_right=true), or it is scanned in the specified order, from pt1 to pt2 (left_to_right=false). The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm.

Initializes matrix header.

Reference to the matrix header to be initialized. Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements.

Initializes matrix header.

Reference to the matrix header to be initialized. Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements. Optional data pointer assigned to the matrix header.

Initializes matrix header.

Reference to the matrix header to be initialized. Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements. Optional data pointer assigned to the matrix header. Full row width in bytes of the data assigned. By default, the minimal possible step is used, i.e., no gaps is assumed between subsequent rows of the matrix.

Initializes multi-dimensional array header.

Reference to the array header to be initialized. Number of array dimensions. Array of dimension sizes. Type of array elements. The same as for CvMat.

Initializes multi-dimensional array header.

Reference to the array header to be initialized. Number of array dimensions. Array of dimension sizes. Type of array elements. The same as for CvMat. Optional data pointer assigned to the matrix header.

Initializes sparse array elements iterator

Input array Initialized iterator the first sparse matrix element

CvSubdiv2Dの初期化

Initializes tree node iterator

Tree iterator initialized by the function. The initial node to start traversing from. The maximal level of the tree (first node assumed to be at the first level) to traverse up to. For example, 1 means that only nodes at the same level as first should be visited, 2 means that the nodes on the same level as first and their direct children should be visited etc.

Pre-computes the undistortion map - coordinates of the corresponding pixel in the distorted image for every pixel in the corrected image.

The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. The output array of x-coordinates of the map. The output array of y-coordinates of the map.

Computes undistortion+rectification transformation map a head of stereo camera

The camera matrix A=[fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1, 1x4, 5x1 or 1x5. The rectification transformation in object space (3x3 matrix). R1 or R2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. The new camera matrix A'=[fx' 0 cx'; 0 fy' cy'; 0 0 1]. The output array of x-coordinates of the map. The output array of y-coordinates of the map.

Inpaints the selected region in the image.

The input 8-bit 1-channel or 3-channel image. The inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted. The output image of the same format and the same size as input. The radius of circlular neighborhood of each point inpainted that is considered by the algorithm. The inpainting method.

Checks that array elements lie between elements of two other arrays

The first source array. The inclusive lower boundary array. The exclusive upper boundary array. The destination array, must have 8u or 8s type.

Checks that array elements lie between two scalars

The first source array. The inclusive lower boundary. The exclusive upper boundary. The destination array, must have 8u or 8s type.

Adds new node to the tree

The inserted node. The parent node that is already in the tree. The top level node. If parent and frame are the same, v_prev field of node is set to null rather than parent.

Calculates integral images.

The source image, WxH, 8-bit or floating-point (32f or 64f) image. The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f).

Calculates integral images.

The source image, WxH, 8-bit or floating-point (32f or 64f) image. The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f).

Calculates integral images.

Finds inverse or pseudo-inverse of matrix

The source matrix. The destination matrix. In case of LU method the function returns src1 determinant (src1 must be square). If it is 0, the matrix is not inverted and src2 is filled with zeros. In case of SVD methods the function returns the inverted condition number of src1

Finds inverse or pseudo-inverse of matrix

The source matrix. The destination matrix. Inversion method In case of LU method the function returns src1 determinant (src1 must be square). If it is 0, the matrix is not inverted and src2 is filled with zeros. In case of SVD methods the function returns the inverted condition number of src1

Finds inverse or pseudo-inverse of matrix

Calculates inverse square root

The input floating-point value

Determines if the argument is Infinity

The input floating-point value

Determines if the argument is Not A Number

The input floating-point value

Adjusts model state

Kalman filter CvMat containing the measurement vector. The function stores adjusted state at kalman->state_post and returns it on output.

Adjusts model state

Kalman filter CvMat containing the measurement vector. The function stores adjusted state at kalman->state_post and returns it on output.

Estimates subsequent model state

Kalman filter state. The function returns the estimated state.

Estimates subsequent model state

Kalman filter state. Control vector (uk), should be null iff there is no external control (control_params=0). The function returns the estimated state.

Estimates subsequent model state

Kalman filter state. The function returns the estimated state.

Estimates subsequent model state

Kalman filter state. Control vector (uk), should be null iff there is no external control (control_params=0). The function returns the estimated state.

Splits set of vectors by given number of clusters

Floating-point matrix of input samples, one row per sample. Number of clusters to split the set by. Output integer vector storing cluster indices for every sample. Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations).

Splits set of vectors by given number of clusters

Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator.

Source image. Destination image.

Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator.

Source image. Destination image. Aperture size (it has the same meaning as in cvSobel).

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

image to detect objects in Latent SVM detector in internal representation memory storage to store the resultant sequence of the object candidate rectangles

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

image to detect objects in Latent SVM detector in internal representation memory storage to store the resultant sequence of the object candidate rectangles threshold for the non-maximum suppression algorithm = 0.5f [here will be the reference to original paper]

find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

Draws a line segment connecting two points

The image. First point's x-coordinate of the line segment. First point's y-coordinate of the line segment. Second point's x-coordinate of the line segment. Second point's y-coordinate of the line segment. Line color.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color. Line thickness.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line. Number of fractional bits in the point coordinates.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color. Line thickness.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line.

Draws a line segment connecting two points

The image. First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line. Number of fractional bits in the point coordinates.

Performs forward or inverse linear-polar image transform

Loads object from file

Object type to load File name. The function cvLoad loads object from file.

Loads object from file

Object type to load File name. Memory storage for dynamic structures, such as CvSeq or CvGraph. It is not used for matrices or images. The function cvLoad loads object from file.

Loads object from file

Object type to load File name. Memory storage for dynamic structures, such as CvSeq or CvGraph. It is not used for matrices or images. Optional object name. If it is NULL, the first top-level object in the storage will be loaded. The function cvLoad loads object from file.

Loads object from file

Loads a trained cascade classifier from file or the classifier database embedded in OpenCV

Name of directory containing the description of a trained cascade classifier. Original size of objects the cascade has been trained on. Note that it is not stored in the cascade and therefore must be specified separately. The function is obsolete. Nowadays object detection classifiers are stored in XML or YAML files, rather than in directories. To load cascade from a file, use cvLoad function.

Loads an image from the specified file and returns the reference to the loaded image.

Name of file to be loaded. the reference to the loaded image.

Loads an image from the specified file and returns the reference to the loaded image.

Name of file to be loaded. Specifies colorness and Depth of the loaded image. the reference to the loaded image.

Loads an image from the specified file and returns the reference to the loaded image as CvMat.

Name of file to be loaded. the reference to the loaded image.

Loads an image from the specified file and returns the reference to the loaded image as CvMat.

Name of file to be loaded. Specifies colorness and Depth of the loaded image. the reference to the loaded image.

load trained detector from a file

Name of file to be loaded.

Load parameters of the window.

Name of the window

Calculates natural logarithm of every array element absolute value

The source array. The destination array, it should have double type or the same type as the source.

Remaps image to log-polar space. The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc.

Source image. Destination image. The transformation center, where the output precision is maximal. Magnitude scale parameter. See below.

Remaps image to log-polar space. The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc.

Source image. Destination image. The transformation center, where the output precision is maximal. Magnitude scale parameter. See below. A combination of interpolation method and the optional flags.

Add vectors to the LSH structure, optionally returning indices.

Query the LSH n times for at most k nearest points; data is n x d, indices and dist are n x k. At most emax stored points will be accessed.

Remove vectors from LSH, as addressed by given indices.

Return the number of vectors in the LSH.

number of vectors

Performs look-up table transform of array

Source array of 8-bit elements. Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array. In case of multi-channel source and destination arrays, the table should either have a single-channel (in this case the same table is used for all channels), or the same number of channels as the source/destination array.

Performs look-up table transform of array

Calculates Mahalanobis distance between two vectors

The first 1D source vector. The second 1D source vector. The inverse covariation matrix. Mahalanobis distance

Calculates Mahalonobis distance between two vectors

The first 1D source vector. The second 1D source vector. The inverse covariation matrix. Mahalonobis distance

Makes a histogram out of array

Number of histogram dimensions. Array of histogram dimension sizes. The histogram header initialized by the function. Array that will be used to store histogram bins.

Makes a histogram out of array

Number of histogram dimensions. Array of histogram dimension sizes. The histogram header initialized by the function. Array that will be used to store histogram bins. Histogram bin ranges, see CreateHist.

Makes a histogram out of array

Calculates scanlines coordinates for two cameras by fundamental matrix

Fundamental matrix. Size of the image. Array of calculated scanlines of the first image. Array of calculated scanlines of the second image. Array of calculated lengths (in pixels) of the first image scanlines. Array of calculated lengths (in pixels) of the second image scanlines. Variable that stores the number of scanlines.

Constructs sequence from array

Type of the created sequence. Size of the header of the sequence. Parameter sequence must point to the structure of that size or greater size. Size of the sequence element. Elements that will form a sequence. Pointer to the local variable that is used as the sequence header. Pointer to the local variable that is the header of the single sequence block.

Initializes matrix header (light-weight variant)

Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements (see CreateMat). The function cvMat is a fast inline substitution for cvInitMatHeader.

Initializes matrix header (light-weight variant)

Number of rows in the matrix. Number of columns in the matrix. Type of the matrix elements (see CreateMat). Optional data pointer assigned to the matrix header. The function cvMat is a fast inline substitution for cvInitMatHeader.

Compares two contours using their tree representations.

First contour tree. Second contour tree. Similarity measure, only I1 is supported. Similarity threshold.

Compares two shapes.

First contour or grayscale image. Second contour or grayscale image. Comparison method.

Compares two shapes.

First contour or grayscale image. Second contour or grayscale image. Comparison method. Method-specific parameter (is not used now).

Compares template against overlapped image regions.

Image where the search is running. It should be 8-bit or 32-bit floating-point. Searched template; must be not greater than the source image and the same data type as the image. A map of comparison results; single-channel 32-bit floating-point. If image is W×H and templ is w×h then result must be W-w+1×H-h+1. Specifies the way the template must be compared with image regions.

Finds per-element maximum of two arrays

The first source array. The second source array. The destination array.

Finds bounding rectangle for two given rectangles

First rectangle Second rectangle

Finds per-element maximum of array and scalar

The first source array. The scalar value. The destination array.

Finds object center on back projection

Allocates memory buffer in the storage

Memory storage. Buffer size.

Allocates text string in the storage

Memory storage The string

Composes multi-channel array from several single-channel arrays or inserts a single channel into the array

Input channel 0 Input channel 1 Input channel 2 Input channel 3 Destination array.

Composes multi-channel array from several single-channel arrays or inserts a single channel into the array

Input channel 0 Input channel 1 Input channel 2 Input channel 3 Destination array.

Return the particular element of single-channel floating-point matrix

Input matrix. The zero-based index of row. The zero-based index of column.

Finds per-element minimum of two arrays

The first source array. The second source array. The destination array.

Finds global minimum and maximum in array or subarray

The source array, single-channel or multi-channel with COI set. Pointer to returned minimum value. Pointer to returned maximum value.

Finds global minimum and maximum in array or subarray

The source array, single-channel or multi-channel with COI set. Pointer to returned minimum value. Pointer to returned maximum value. The optional mask that is used to select a subarray.

Finds global minimum and maximum in array or subarray

The source array, single-channel or multi-channel with COI set. Pointer to returned minimum location. Pointer to returned maximum location.

Finds global minimum and maximum in array or subarray

The source array, single-channel or multi-channel with COI set. Pointer to returned minimum location. Pointer to returned maximum location. The optional mask that is used to select a subarray.

Finds global minimum and maximum in array or subarray

The source array, single-channel or multi-channel with COI set. Pointer to returned minimum value. Pointer to returned maximum value. Pointer to returned minimum location. Pointer to returned maximum location.

Finds global minimum and maximum in array or subarray

Finds circumscribed rectangle of minimal area for given 2D point set

Sequence or array of points. The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull.

Finds circumscribed rectangle of minimal area for given 2D point set

Sequence or array of points. The point tested against the contour. The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull.

Finds circumscribed rectangle of minimal area for given 2D point set

Sequence or array of 2D points. Output parameter. The center of the enclosing circle. Output parameter. The radius of the enclosing circle. The function cvMinEnclosingCircle finds the minimal circumscribed circle for 2D point set using iterative algorithm. It returns true if the resultant circle contains all the input points and false otherwise (i.e. algorithm failed).

Finds circumscribed rectangle of minimal area for given 2D point set

Finds per-element minimum of array and scalar

The first source array. The scalar value. The destination array.

Copies several channels from input arrays to certain channels of output arrays

The array of input arrays. The array of output arrays. The array of pairs of indices of the planes copied. from_to[k*2] is the 0-based index of the input plane, and from_to[k*2+1] is the index of the output plane, where the continuous numbering of the planes over all the input and over all the output arrays is used. When from_to[k*2] is negative, the corresponding output plane is filled with 0's.

Moments

Image (1-channel or 3-channel with COI set) or polygon (CvSeq of points or a vector of points) Returned moment state structure (For images only) If the flag is non-zero, all the zero pixel values are treated as zeroes, all the others are treated as 1’s

Performs advanced morphological transformations using erosion and dilation as basic operations.

Source image. Destination image. Temporary image, required in some cases. Structuring element. Type of morphological operation.

Performs advanced morphological transformations using erosion and dilation as basic operations.

Source image. Destination image. Temporary image, required in some cases. Structuring element. Type of morphological operation. Number of times erosion and dilation are applied.

Changes position of the window.

Name of the window to be resized. New x coordinate of top-left corner New y coordinate of top-left corner

Creates MSER parameters

delta, in the code, it compares (size_{i}-size_{i-delta})/size_{i-delta} prune the area which smaller than min_area prune the area which bigger than max_area prune the area have simliar size to its children trace back to cut off mser with diversity < min_diversity for color image, the evolution steps the area threshold to cause re-initialize ignore too small margin the aperture size for edge blur

Return the particular element of single-channel floating-point matrix

The matrix. The zero-based index of row. The zero-based index of column. The new value of the matrix element

Calculates per-element product of two arrays

The first source array. The second source array. The destination array.

Calculates per-element product of two arrays

The first source array. The second source array. The destination array. Optional scale factor

Performs per-element multiplication of two Fourier spectrums

The first source array. The second source array. The destination array of the same type and the same size of the sources.

Adds product of two input images to accumulator

First input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). Second input image, the same format as the first one. Accumulator of the same number of channels as input images, 32-bit or 64-bit floating-point.

Adds product of two input images to accumulator

Calculates product of array and transposed array

The source matrix. The destination matrix. Order of multipliers.

Calculates product of array and transposed array

The source matrix. The destination matrix. Order of multipliers. An optional array, subtracted from src before multiplication.

Calculates product of array and transposed array

The source matrix. The destination matrix. Order of multipliers. An optional array, subtracted from src before multiplication.

Creates a window which can be used as a placeholder for images and trackbars. Created windows are reffered by their names.

Name of the window which is used as window identifier and appears in the window caption.

Creates a window which can be used as a placeholder for images and trackbars. Created windows are reffered by their names.

Name of the window which is used as window identifier and appears in the window caption. Flags of the window. Currently the only supported flag is WindowMode.AutoSize. If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually.

Returns index of graph vertex

Graph traversal state. It is updated by the function. The function cvNextGraphItem traverses through the graph until an event interesting to the user (that is, an event, specified in the mask in cvCreateGraphScanner call) is met or the traversal is over. In the first case it returns one of the events, listed in the description of mask parameter above and with the next call it resumes the traversal. In the latter case it returns CV_GRAPH_OVER (-1). When the event is CV_GRAPH_VERTEX, or CV_GRAPH_BACKTRACKING or CV_GRAPH_NEW_TREE, the currently observed vertex is stored in scanner->vtx. And if the event is edge-related, the edge itself is stored at scanner->edge, the previously visited vertex - at scanner->vtx and the other ending vertex of the edge - at scanner->dst.

Moves iterator to the next line point

LineIterator object

Returns the currently observed node and moves iterator toward the next node

Tree iterator initialized by the function.

Returns the currently observed node and moves iterator toward the next node

Tree iterator initialized by the function.

Returns the currently observed node and moves iterator toward the next node

Tree iterator initialized by the function.

Calculates absolute array norm, absolute difference norm or relative difference norm

The first source image.

Calculates absolute array norm, absolute difference norm or relative difference norm

The first source image. The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated.

Calculates absolute array norm, absolute difference norm or relative difference norm

The first source image. The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. Type of norm

Calculates absolute array norm, absolute difference norm or relative difference norm

The first source image. The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. Type of norm The optional operation mask.

Normalizes array to a certain norm or value range

The input array. The output array; in-place operation is supported.

Normalizes array to a certain norm or value range

The input array. The output array; in-place operation is supported. The minimum/maximum value of the output array or the norm of output array. The maximum/minimum value of the output array.

Normalizes array to a certain norm or value range

The input array. The output array; in-place operation is supported. The minimum/maximum value of the output array or the norm of output array. The maximum/minimum value of the output array. The normalization type.

Normalizes array to a certain norm or value range

Normalizes the histogram bins by scaling them, such that the sum of the bins becomes equal to factor.

Reference to the histogram. Threshold level.

Performs per-element bit-wise inversion of array elements

The source array. The destination array.

Opens file storage for reading or writing data

Name of the file associated with the storage. Memory storage used for temporary data and for storing dynamic structures, such as CvSeq or CvGraph. If it is null, a temporary memory storage is created and used. pointer to CvFileStorage structure.

Opens file storage for reading or writing data

Calculates per-element bit-wise disjunction of two arrays

The first source array. The second source array. The destination array.

Calculates per-element bit-wise disjunction of two arrays

The first source array. The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Calculates per-element bit-wise disjunction of array and scalar

The source array. Scalar to use in the operation. The destination array.

Calculates per-element bit-wise disjunction of array and scalar

The source array. Scalar to use in the operation. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Performs perspective matrix transform of vector array

The source three-channel floating-point array. The destination three-channel floating-point array. 3×3 or 4×4 transformation matrix.

Creates 2D point with integer coordinates

x-coordinate, usually zero-based y-coordinate, usually zero-based

Creates 2D point with floating-point coordinates

x-coordinate, usually zero-based y-coordinate, usually zero-based

Creates 2D point with double precision floating-point coordinates

x-coordinate, usually zero-based y-coordinate, usually zero-based

Creates3D point with floating-point coordinates

x-coordinate, usually zero-based y-coordinate, usually zero-based z-coordinate, usually zero-based

Creates 3D point with double precision floating-point coordinates

x-coordinate, usually zero-based y-coordinate, usually zero-based z-coordinate, usually zero-based

Point in contour test

Input contour. The point tested against the contour. If it is true, the function estimates distance from the point to the nearest contour edge. The function cvPointPolygonTest determines whether the point is inside contour, outside, or lies on an edge (or coinsides with a vertex). It returns positive, negative or zero value, correspondingly. When measureDist=0, the return value is +1, -1 and 0, respectively. When measureDist≠0, it is a signed distance between the point and the nearest contour edge.

Initializes point sequence header from a point vector

Type of the point sequence. Input matrix. It should be continuous 1-dimensional vector of points, that is, it should have type CV_32SC2 or CV_32FC2. Contour header, initialized by the function. Sequence block header, initialized by the function.

Calculates cartesian coordinates of 2d vectors represented in polar form

The array of magnitudes. If it is null, the magnitudes are assumed all 1’s. The array of angles, whether in radians or degrees. The destination array of x-coordinates, may be set to null if it is not needed. The destination array of y-coordinates, mau be set to null if it is not needed.

Calculates cartesian coordinates of 2d vectors represented in polar form

Draws simple or thick polygons

Image. Array of pointers to polylines. Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. Polyline color. Thickness of the polyline edges.

Draws simple or thick polygons

Implements POSIT algorithm

Posit object structure. Object points projections on the 2D image plane. Focal length of the camera used. Termination criteria of the iterative POSIT algorithm. Matrix of rotations. Translation vector.

Raises every array element to power

The source array. The destination array, should be the same type as the source. The exponent of power.

Calculates feature map for corner detection

Input image. Image to store the corner candidates.

Calculates feature map for corner detection

Input image. Image to store the corner candidates. Aperture parameter for Sobel operator.

Returns the currently observed node and moves iterator toward the previous node

Tree iterator initialized by the function.

Returns the currently observed node and moves iterator toward the previous node

Tree iterator initialized by the function.

Returns the currently observed node and moves iterator toward the previous node

Tree iterator initialized by the function.

Projects vectors to the specified subspace

The input data; each vector is either a single row or a single column. The mean (average) vector. If it is a single-row vector, it means that the output vectors are stored as rows of result; otherwise, it should be a single-column vector, then the vectors are stored as columns of result. The eigenvectors (principal components); one vector per row. The output matrix of decomposition coefficients. The number of rows must be the same as the number of vectors, the number of columns must be less than or equal to the number of rows in eigenvectors. That it is less, the input vectors are projected into subspace of the first cols(result) principal components.

Computes projections of 3D points to the image plane given intrinsic and extrinsic camera parameters. Optionally, the function computes jacobians - matrices of partial derivatives of image points as functions of all the input parameters w.r.t. the particular parameters, intrinsic and/or extrinsic.

Note, that with intrinsic and/or extrinsic parameters set to special values, the function can be used to compute just extrinsic transformation or just intrinsic transformation (i.e. distortion of a sparse set of points). The array of object points, 3xN or Nx3, where N is the number of points in the view. The rotation vector, 1x3 or 3x1. The translation vector, 1x3 or 3x1. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is null, all distortion coefficients are considered 0's. The output array of image points, 2xN or Nx2, where N is the total number of points in the view. Optional Nx3 matrix of derivatives of image points with respect to components of the rotation vector. Optional Nx3 matrix of derivatives of image points w.r.t. components of the translation vector. Optional Nx2 matrix of derivatives of image points w.r.t. fx and fy. Optional Nx2 matrix of derivatives of image points w.r.t. cx and cy. Optional Nx4 matrix of derivatives of image points w.r.t. distortion coefficients.

Return pointer to the particular array element

Input array. The first zero-based component of the element index pointer to the particular array element

Return pointer to the particular array element

Input array. The first zero-based component of the element index Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index pointer to the particular array element

Return pointer to the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index pointer to the particular array element

Return pointer to the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

Input array. Array of the element indices pointer to the particular array element

Return pointer to the particular array element

Input array. Array of the element indices Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

Input array. Array of the element indices Type of matrix elements Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. Optional input parameter for sparse matrices. If the pointer is not NULL, the function does not recalculate the node hash value, but takes it from the specified location. It is useful for speeding up pair-wise operations pointer to the particular array element

Draws text string

Input image. String to print. Coordinates of the bottom-left corner of the first letter. Pointer to the font structure. Text color.

Downsamples image.

The source image. The destination image, should have 2x smaller width and height than the source.

Downsamples image.

The source image. The destination image, should have 2x smaller width and height than the source. Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported.

Does meanshift image segmentation.

The source 8-bit 3-channel image. The destination image of the same format and the same size as the source. The spatial window radius. The color window radius.

Does meanshift image segmentation.

The source 8-bit 3-channel image. The destination image of the same format and the same size as the source. The spatial window radius. The color window radius. Maximum level of the pyramid for the segmentation.

Does meanshift image segmentation.

Does image segmentation by pyramids.

The source image. The destination image.

Does image segmentation by pyramids.

The source image. The destination image. Storage; stores the resulting sequence of connected components. Pointer to the output sequence of the segmented components. Maximum level of the pyramid for the segmentation. Error threshold for establishing the links. Error threshold for the segments clustering.

Upsamples image.

The source image. The destination image, should have 2x smaller width and height than the source.

Upsamples image.

The source image. The destination image, should have 2x smaller width and height than the source. Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported.

Grabs a frame from camera or video file, decompresses and returns it. This function is just a combination of cvGrabFrame and cvRetrieveFrame in one call. The returned image should not be released or modified by user.

video capturing structure.

Queries value of histogram bin.

Histogram. 1st index of the bin.

Queries value of histogram bin.

Histogram. 1st index of the bin. 2nd index of the bin.

Queries value of histogram bin.

Histogram. 1st index of the bin. 2nd index of the bin. 3rd index of the bin.

Queries value of histogram bin.

1st index of the bin. Array of indices.

Implements a particular case of application of line iterators. The function reads all the image points lying on the line between pt1 and pt2, including the ending points, and stores them into the buffer.

Image to sample the line from. Starting the line point. Ending the line point. Buffer to store the line points. The line connectivity, 4 or 8.

Saves object to file

File name. Object to save.

Saves object to file

File name. Object to save. Optional object name. If it is null, the name will be formed from filename.

Saves object to file

File name. Object to save. Optional object name. If it is null, the name will be formed from filename. Optional comment to put in the beginning of the file.

Saves object to file

File name. Object to save. Optional object name. If it is null, the name will be formed from filename. Optional comment to put in the beginning of the file. Optional attributes passed to cvWrite.

Saves object to file

Object to save. File name.

Saves object to file

Object to save. File name. Optional object name. If it is null, the name will be formed from filename.

Saves object to file

Object to save. File name. Optional object name. If it is null, the name will be formed from filename. Optional comment to put in the beginning of the file.

Saves object to file

Object to save. File name. Optional object name. If it is null, the name will be formed from filename. Optional comment to put in the beginning of the file. Optional attributes passed to cvWrite.

Saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function.

Name of the file. Image to be saved.

Saves memory storage position

Memory storage. The output position of the storage top.

Save parameters of the window.

Name of the window

Initializes val[0]...val[3] with val0123

Calculates sum of scaled array and another array

The first source array. Scale factor for the first array. The second source array. The destination array

Calculates sum of scaled array and another array

The first source array. Scale factor for the first array. The second source array. The destination array

cvScaleAdd(A, cvRealScalar(real_scalar), B, C)

Segments whole motion into separate moving parts

Motion history image. Image where the mask found should be stored, single-channel, 32-bit floating-point. Memory storage that will contain a sequence of motion connected components. Current time in milliseconds or other units. Segmentation threshold; recommended to be equal to the interval between motion history "steps" or greater.

Returns index of concrete sequence element

Element type Sequence. the element within the sequence. the index of a sequence element or a negative number if the element is not found.

Returns index of concrete sequence element

Element type Sequence. the element within the sequence. the address of the sequence block that contains the element is stored in this location. the index of a sequence element or a negative number if the element is not found.

Inserts element in sequence middle

Element type Sequence. Index before which the element is inserted. Inserting before 0 (the minimal allowed value of the parameter) is equal to cvSeqPushFront and inserting before seq->total (the maximal allowed value of the parameter) is equal to cvSeqPush. Inserted element. Inserted element.

Inserts array in the middle of sequence

Sequence. The part of the sequence to remove. The array to take elements from.

Reverses the order of sequence elements

Sequence.

Removes element from sequence middle

Sequence. Index of removed element.

Removes sequence slice

Sequence. The part of the sequence to remove.

Splits sequence into equivalence classes

The sequence to partition. The storage to store the sequence of equivalence classes. If it is null, the function uses seq->storage for output labels. Output parameter. Double pointer to the sequence of 0-based labels of input sequence elements. The relation function that should return non-zero if the two particular sequence elements are from the same class, and zero otherwise. The partitioning algorithm uses transitive closure of the relation function as equivalence criteria.

Splits sequence into equivalence classes

Removes element from sequence end

Sequence.

Removes element from sequence end

Element type Sequence. copied the removed element to this location.

Removes element from sequence beginning

Sequence.

Removes element from sequence beginning

Element type Sequence. copied the removed element to this location.

Removes several elements from the either end of sequence

Element type Sequence. Removed elements. Number of elements to pop. The flags specifying the modified sequence end

allocates a space for one more element.

Sequence. pointer to the allocated element.

Adds element to sequence end

Element type Sequence. Added element. pointer to the allocated element.

Adds element to sequence beginning

Sequence. pointer to the added element

Adds element to sequence beginning

Element type Sequence. Added element. pointer to the added element

Pushes several elements to the either end of sequence

Element type Sequence. Added elements. The flags specifying the modified sequence end

Searches element in sequence

The sequence The element to look for The comparison function that returns negative, zero or positive value depending on the elements relation Whether the sequence is sorted or not. Output parameter; index of the found element.

Searches element in sequence

Element type The sequence The element to look for The comparison function that returns negative, zero or positive value depending on the elements relation Whether the sequence is sorted or not. Output parameter; index of the found element.

Makes separate header for the sequence slice

Sequence. The part of the sequence to extract.

Makes separate header for the sequence slice

Sequence. The part of the sequence to extract. The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. The flag that indicates whether to copy the elements of the extracted slice (copy_data=true) or not (copy_data=false)

Makes separate header for the sequence slice

Element type Sequence. The part of the sequence to extract.

Makes separate header for the sequence slice

Element type Sequence. The part of the sequence to extract. The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. The flag that indicates whether to copy the elements of the extracted slice (copy_data=true) or not (copy_data=false)

Sorts sequence element using the specified comparison function

The sequence to sort The comparison function that returns negative, zero or positive value depending on the elements relation (see the above declaration and the example below) - similar function is used by qsort from C runtime except that in the latter userdata is not used

Sorts sequence element using the specified comparison function

Element type The sequence to sort The comparison function that returns negative, zero or positive value depending on the elements relation (see the above declaration and the example below) - similar function is used by qsort from C runtime except that in the latter userdata is not used

Sets every element of array to given value

The destination array. Fill value.

Sets every element of array to given value

The destination array. Fill value. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Change the particular array element

Input array. The first zero-based component of the element index The assigned value

Change the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The assigned value

Change the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index The assigned value

Change the particular array element

Input array. The assigned value Array of the element indices

Occupies a node in the set

Set. the index to the node

Occupies a node in the set

Set. Optional input argument, inserted element. If not null, the function copies the data to the allocated node (The MSB of the first integer field is cleared after copying). the index to the node

Occupies a node in the set

Set. Optional input argument, inserted element. If not null, the function copies the data to the allocated node (The MSB of the first integer field is cleared after copying). Optional output argument; the pointer to the allocated cell. the index to the node

Sets bounds of histogram bins

Histogram. Array of bin ranges arrays.

Sets bounds of histogram bins

Histogram. Array of bin ranges arrays. Uniformity flag.

Sets the specified property of video capturing.

video capturing structure. property identifier. value of the property.

Sets the specified property of video capturing.

video capturing structure. property identifier. value of the property.

Assigns user data to the array header. Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function.

Array header. User data. Full row length in bytes.

Assigns user data to the array header. Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function.

Array header. User data. Full row length in bytes.

Sets error processing mode, returns previously used mode

The error mode. previously used mode

Sets the error status

The error status.

Initializes scaled identity matrix

The matrix to initialize (not necessarily square).

Initializes scaled identity matrix

The matrix to initialize (not necessarily square). The value to assign to the diagonal elements.

Sets channel of interest to given value. Value 0 means that all channels are selected, 1 means that the first channel is selected etc.

Image header. Channel of interest.

Sets image ROI to given rectangle

Image header. ROI rectangle.

Assigns images to the hidden cascade

Hidden Haar classifier cascade, created by cvCreateHidHaarClassifierCascade. Integral (sum) single-channel image of 32-bit integer format. This image as well as the two subsequent images are used for fast feature evaluation and brightness/contrast normalization. They all can be retrieved from input 8-bit or floating point single-channel image using The function cvIntegral. Square sum single-channel image of 64-bit floating-point format. Tilted sum single-channel image of 32-bit integer format. Window scale for the cascade. If scale=1, original window size is used (objects of that size are searched) - the same size as specified in cvLoadHaarClassifierCascade (24x24 in case of "<default_face_cascade>"), if scale=2, a two times larger window is used (48x48 in case of default face cascade). While this will speed-up search about four times, faces smaller than 48x48 cannot be detected.

Sets the callback function for mouse events occuting within the specified window.

Name of the window. Reference to the function to be called every time mouse event occurs in the specified window.

Adds element to set (fast variant)

Set. pointer to a new node

Sets the number of threads.

The number of threads. When the argument is zero or negative, and at the beginning of the program, the number of threads is set to the number of processors in the system, as returned by the function omp_get_num_procs() from OpenMP runtime.

Change the particular array element

Input array. The first zero-based component of the element index The assigned value

Change the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The assigned value

Change the particular array element

Input array. The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index The assigned value

Change the particular array element

Input array. The assigned value Array of the element indices

Removes element from set

Set. Index of the removed element.

Removes set element given its pointer

Set. Removed element.

Sets up sequence block size

Sequence. Desirable sequence block size in elements.

Moves the reader to specified position

Reader state. The destination position. If the positioning mode is used (see the next parameter) the actual position will be index mod reader->seq->total.

Moves the reader to specified position

Reader state. The destination position. If the positioning mode is used (see the next parameter) the actual position will be index mod reader->seq->total. If it is true, then index is a relative to the current position.

Sets the position of the specified trackbar.

Name of trackbar. Name of the window which is the parent of trackbar. New position.

Set Property of the window

Window name Property identifier New value of the specified property

Clears the array

array to be cleared.

Clears the array

array to be cleared.

Shows the image in the specified window. If the window was created with CV_WINDOW_AUTOSIZE flag then the image is shown with its original size, otherwise the image is scaled to fit the window.

Name of the window. Image to be shown.

Create CVSize structure and initializes it

Width Height

Calculates the sequence slice length

Slice to measure Sequence

Smooths the image in one of several ways.

The source image. The destination image.

Smooths the image in one of several ways.

The source image. The destination image. Type of the smoothing.

Smooths the image in one of several ways.

The source image. The destination image. Type of the smoothing. The first parameter of smoothing operation.

Smooths the image in one of several ways.

The source image. The destination image. Type of the smoothing. The first parameter of smoothing operation. The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. In case of Gaussian kernel this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size.

Smooths the image in one of several ways.

Changes contour position to minimize its energy

The source image or external energy field. Contour points (snake). Weight of continuity energy, single float or array of length floats, one per each contour point. Weight of curvature energy, similar to alpha. Weight of image energy, similar to alpha. Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. Termination criteria. Gradient flag. If true, the function calculates gradient magnitude for every image pixel and consideres it as the energy field, otherwise the input image itself is considered.

Changes contour position to minimize its energy

The source image or external energy field. Contour points (snake). Weights of continuity energy, single float or array of length floats, one per each contour point. Weights of curvature energy, similar to alpha. Weights of image energy, similar to alpha. Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. Termination criteria. Gradient flag. If true, the function calculates gradient magnitude for every image pixel and consideres it as the energy field, otherwise the input image itself is considered.

Calculates first, second, third or mixed image derivatives using _extended Sobel operator

Source image. Destination image. Order of the derivative x. Order of the derivative y.

Calculates first, second, third or mixed image derivatives using extended Sobel operator

Source image. Destination image. Order of the derivative x. Order of the derivative y. Size of the extended Sobel kernel.

Solves linear system or least-squares problem

The source matrix. The right-hand part of the linear system. The output solution. If CV_LU method is used, the function returns true if src1 is non-singular and false otherwise, in the latter case dst is not valid

Solves linear system or least-squares problem

The source matrix. The right-hand part of the linear system. The output solution. The solution (matrix inversion) method If CV_LU method is used, the function returns true if src1 is non-singular and false otherwise, in the latter case dst is not valid

Finds real roots of a cubic equation

The equation coefficients, array of 3 or 4 elements. The output array of real roots. Should have 3 elements. the number of real roots found.

Finds real and complex roots of a polynomial equation with real coefficients

The (degree + 1)-length array of equation coefficients (CV_32FC1 or CV_64FC1). The degree-length output array of real or complex roots (CV_32FC2 or CV_64FC2).

Finds real and complex roots of a polynomial equation with real coefficients

The (degree + 1)-length array of equation coefficients (CV_32FC1 or CV_64FC1). The degree-length output array of real or complex roots (CV_32FC2 or CV_64FC2). The maximum number of iterations.

Finds real and complex roots of a polynomial equation with real coefficients

The (degree + 1)-length array of equation coefficients (CV_32FC1 or CV_64FC1). The degree-length output array of real or complex roots (CV_32FC2 or CV_64FC2). The maximum number of iterations. The required figures of precision required.

Sorts the rows/cols of an array ascending/descending

Source array to sort

Sorts the rows/cols of an array ascending/descending

Source array to sort Optional destination array

Sorts the rows/cols of an array ascending/descending

Source array to sort Optional destination array Index matrix

Sorts the rows/cols of an array ascending/descending

Source array to sort Optional destination array Index matrix Sorting parameter

Divides multi-channel array into several single-channel arrays or extracts a single channel from the array

Source array. Destination channel 0 Destination channel 1 Destination channel 2 Destination channel 3

Divides multi-channel array into several single-channel arrays or extracts a single channel from the array

Source array. Destination channel 0 Destination channel 1 Destination channel 2 Destination channel 3

Calculates square root

The input floating-point value

Adds the square of source image to accumulator

Input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point.

Adds the square of source image to accumulator

Constructor

Initializes process of writing data to sequence

Pointer to the sequence. Writer state; initialized by the function.

Initializes contour scanning process

The source 8-bit single channel binary image. Container of the retrieved contours. CvContourScanner

Initializes contour scanning process

The source 8-bit single channel binary image. Container of the retrieved contours. Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. Retrieval mode; see cvFindContours. Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. CvContourScanner

Initializes contour scanning process

Starts the next stream

File storage.

Pointer to chain. Chain reader state.

Initializes file node sequence reader

File storage. The file node (a sequence) to read numbers from. Output reference to the sequence reader.

Initializes process of sequential reading from sequence

Sequence. Reader state; initialized by the function.

Initializes process of sequential reading from sequence

Sequence. Reader state; initialized by the function. Determines the direction of the sequence traversal. If reverse is false, the reader is positioned at the first sequence element, otherwise it is positioned at the last element.

For MacOS or Linux, tries to start thread to hande a window automatically (resizing, updating). Returns 0 if not supported

Creates new sequence and initializes writer for it

Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be equal to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. Size of the sequence header. The parameter value may not be less than sizeof(CvSeq). If a certain type or extension is specified, it must fit the base type header. Size of the sequence elements in bytes; must be consistent with the sequence type. For example, if the sequence of points is created (element type CV_SEQ_ELTYPE_POINT ), then the parameter elem_size must be equal to sizeof(CvPoint). Sequence location. Writer state; initialized by the function.

Starts writing a new structure

File storage. Name of the written structure. The structure can be accessed by this name when the storage is read. A combination one of the NodeType flags

Starts writing a new structure

File storage. Name of the written structure. The structure can be accessed by this name when the storage is read. A combination one of the NodeType flags Optional parameter - the object type name. In case of XML it is written as type_id attribute of the structure opening tag. In case of YAML it is written after a colon following the structure name. Mainly it comes with user objects. When the storage is read, the encoded type name is used to determine the object type.

Calibrates stereo camera

The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. The joint matrix of corresponding image points in the views from the 1st camera, 2xN or Nx2, where N is the total number of points in all views. The joint matrix of corresponding image points in the views from the 2nd camera, 2xN or Nx2, where N is the total number of points in all views. Vector containing numbers of points in each view, 1xM or Mx1, where M is the number of views. The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. Size of the image, used only to initialize intrinsic camera matrix. The rotation matrix between the 1st and the 2nd cameras' coordinate systems The translation vector between the cameras' coordinate systems.

Calibrates stereo camera

Computes rectification transform for stereo camera

The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. Size of the image used for stereo calibration. The rotation matrix between the 1st and the 2nd cameras' coordinate systems The translation vector between the cameras' coordinate systems. 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively 3x4 Projection matrices in the new (rectified) coordinate systems 3x4 Projection matrices in the new (rectified) coordinate systems

Computes rectification transform for stereo camera

Computes rectification transform for uncalibrated stereo camera

The 2 arrays of corresponding 2D points. The 2 arrays of corresponding 2D points. Fundamental matrix. It can be computed using the same set of point pairs points1 and points2 using cvFindFundamentalMat Size of the image. The rectification homography matrices for the first and for the second images. The rectification homography matrices for the first and for the second images. Optional threshold used to filter out the outliers. If the parameter is greater than zero, then all the point pairs that do not comply the epipolar geometry well enough (that is, the points for which fabs(points2[i]T*F*points1[i])>threshold) are rejected prior to computing the homographies.

Computes per-element difference between two arrays

The first source array. The second source array. The destination array.

Computes per-element difference between two arrays

The first source array. The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Computes difference between array and scalar

The source array. Subtracted scalar. The destination array.

Computes difference between array and scalar

The source array. Subtracted scalar. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Computes difference between scalar and array

The first source array. Scalar to subtract from. The destination array.

Computes difference between scalar and array

The first source array. Scalar to subtract from. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Summarizes array elements

The array. sum S of array elements, independently for each channel

Returns edge destination.

Subdivision edge (not a quad-edge) The edge destination. If the edge is from dual subdivision and the virtual point coordinates are not calculated yet, the returned pointer may be null.

Returns edge origin.

Subdivision edge (not a quad-edge) The edge origin. If the edge is from dual subdivision and the virtual point coordinates are not calculated yet, the returned pointer may be null.

Returns one of edges related to given.

Subdivision edge (not a quad-edge) Specifies, which of related edges to return one the edges related to the input edge

Inserts a single point to Delaunay triangulation

Delaunay or another subdivision. The point to locate. The output edge the point falls onto or right to.

Inserts a single point to Delaunay triangulation

Delaunay or another subdivision. The point to locate. The output edge the point falls onto or right to. Optional output vertex double pointer the input point coinsides with.

Returns another edge of the same quad-edge

Subdivision edge (not a quad-edge) Specifies, which of edges of the same quad-edge as the input one to return one the edges of the same quad-edge as the input edge.

Inserts a single point to Delaunay triangulation

Delaunay subdivision created by function cvCreateSubdivDelaunay2D. Inserted point.

Replaces retrieved contour

Contour scanner initialized by the function cvStartFindContours . Substituting contour.

Creates SURF default parameters

Only features with keypoint.hessian larger than that are extracted. false means basic descriptors (64 elements each), true means _extended descriptors (128 elements each) default parameters

Performs singular value back substitution

Matrix or vector of singular values. Left orthogonal matrix (transposed, perhaps) Right orthogonal matrix (transposed, perhaps) The matrix to multiply the pseudo-inverse of the original matrix A by. This is the optional parameter. If it is omitted then it is assumed to be an identity matrix of an appropriate size (So X will be the reconstructed pseudo-inverse of A). The destination matrix: result of back substitution. Operation flags, should match exactly to the flags passed to cvSVD.

Performs singular value decomposition of real floating-point matrix

Source M×N matrix. Resulting singular value matrix (M×N or N×N) or vector (N×1).

Performs singular value decomposition of real floating-point matrix

Source M×N matrix. Resulting singular value matrix (M×N or N×N) or vector (N×1). Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped.

Performs singular value decomposition of real floating-point matrix

Creates termination criteria for iterative algorithms.

A combination of Iteration and Epsilon Maximum number of iterations Required accuracy

Clears histogram bins that are below the specified threshold.

Reference to the histogram. Threshold level.

Applies fixed-level threshold to array elements.

Source array (single-channel, 8-bit of 32-bit floating point). Destination array; must be either the same type as src or 8-bit. Threshold value. Maximum value to use with CV_THRESH_BINARY and CV_THRESH_BINARY_INV thresholding types. Thresholding type.

Returns trace of matrix

The source matrix. sum of diagonal elements of the matrix src1

Performs matrix transform of every array element

The first source array. The destination array. Transformation matrix.

Performs matrix transform of every array element

The first source array. The destination array. Transformation matrix. Optional shift vector.

Performs matrix transform of every array element

The first source array. The destination array. Transformation matrix.

Performs matrix transform of every array element

The first source array. The destination array. Transformation matrix. Optional shift vector.

Transposes matrix

The source matrix. The destination matrix.

Transposes matrix

The source matrix. The destination matrix.

Gathers all node pointers to the single sequence

The initial tree node. Header size of the created sequence (sizeof(CvSeq) is the most used value). Container for the sequence.

Returns type of the object

The object pointer.

Returns type of the object

The OpenCV object.

Transforms image to compensate lens distortion.

The input (distorted) image. The output (corrected) image. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2].

Transforms image to compensate lens distortion.

The input (distorted) image. The output (corrected) image. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2].

Computes the ideal point coordinates from the observed point coordinates

The observed point coordinates. The ideal point coordinates, after undistortion and reverse perspective transformation. The camera matrix A=[fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1, 1x4, 5x1 or 1x5. The rectification transformation in object space (3x3 matrix). R1 or R2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. The new camera matrix (3x3) or the new projection matrix (3x4). P1 or P2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used.

Unregisters the type

Name of the unregistered type.

Updates motion history image by moving silhouette

Silhouette mask that has non-zero pixels where the motion occurs. Motion history image, that is updated by the function (single-channel, 32-bit floating-point) Current time in milliseconds or other units. Maximal duration of motion track in the same units as timestamp.

Switches between optimized/non-optimized modes

Use optimized (true) or not (false). the number of optimized functions loaded

Waits for key event infinitely (delay<=0) or for "delay" milliseconds. Returns the code of the pressed key or -1 if no key were pressed until the specified timeout has elapsed.

key code

Waits for key event infinitely (delay<=0) or for "delay" milliseconds. Returns the code of the pressed key or -1 if no key were pressed until the specified timeout has elapsed.

Delay in milliseconds. key code

Applies affine transformation to the image.

Source image. Destination image. 2x3 transformation matrix.

Applies affine transformation to the image.

Source image. Destination image. 2x3 transformation matrix. A combination of interpolation method and the optional flags.

Applies affine transformation to the image.

Source image. Destination image. 2x3 transformation matrix. A combination of interpolation method and the optional flags. A value used to fill outliers.

Applies perspective transformation to the image.

Source image. Destination image. 3x3 transformation matrix.

Applies perspective transformation to the image.

Source image. Destination image. 3x3 transformation matrix. A combination of interpolation method and the optional flags.

Applies perspective transformation to the image.

Source image. Destination image. 3x3 transformation matrix. A combination of interpolation method and the optional flags. A value used to fill outliers.

Does watershed segmentation.

The input 8-bit 3-channel image. The input/output 32-bit single-channel image (map) of markers.

Writes user object

File storage. Name, of the written object. Should be null if and only if the parent structure is a sequence. Pointer to the object.

Writes user object

File storage. Name, of the written object. Should be null if and only if the parent structure is a sequence. Pointer to the object. The attributes of the object. They are specific for each particular type.

Writes comment

File storage. The written comment, single-line or multi-line.

Writes comment

File storage. The written comment, single-line or multi-line. If true, the function tries to put the comment in the end of current line. If the flag is false, if the comment is multi-line, or if it does not fit in the end of the current line, the comment starts from a new line.

Writes file node to another file storage

Destination file storage. New name of the file node in the destination file storage. To keep the existing name, use cvGetFileNodeName(node). The written node If the written node is a collection and this parameter is true, no extra level of hierarchy is created. Instead, all the elements of node are written into the currently written structure. Of course, map elements may be written only to map, and sequence elements may be written only to sequence.

Writes/appends one frame to video file.

video writer structure. the written frame.

Writes an integer value

File storage. Name of the written value. Should be NULL if and only if the parent structure is a sequence. The written value.

Writes multiple numbers

Type of the elements in src File storage. Written array Format

Writes a floating-point value

File storage. Name of the written value. Should be null if and only if the parent structure is a sequence. The written value.

Writes a text string

File storage. Name of the written string. Should be null if and only if the parent structure is a sequence. The written text string.

Writes a text string

File storage. Name of the written string. Should be null if and only if the parent structure is a sequence. The written text string. If true, the written string is put in quotes, regardless of whether they are required or not. Otherwise, if the flag is false, quotes are used only when they are required (e.g. when the string starts with a digit or contains spaces).

Performs per-element bit-wise "exclusive or" operation on two arrays

The first source array. The second source array. The destination array. am>

Performs per-element bit-wise "exclusive or" operation on two arrays

The first source array. The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Performs per-element bit-wise "exclusive or" operation on array and scalar

The source array. Scalar to use in the operation. The destination array.

Performs per-element bit-wise "exclusive or" operation on array and scalar

The source array. Scalar to use in the operation. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Decrements array data reference counter．

Input array.

Returns determinant of matrix

The source matrix. determinant of the square matrix mat

Performs forward or inverse Discrete Cosine transform of 1D or 2D floating-point array

Source array, real 1D or 2D array. Destination array of the same size and same type as the source. Transformation flags.

Decode image stored in the buffer

The input array of vector of bytes Specifies color type of the loaded image

Decode image stored in the buffer

The input array of vector of bytes Specifies color type of the loaded image

Computes projection matrix decomposition

The 3x4 input projection matrix P The output 3x3 internal calibration matrix K The output 3x3 external rotation matrix R The output 4x1 external homogenious position vector C

Computes projection matrix decomposition

The 3x4 input projection matrix P The output 3x3 internal calibration matrix K The output 3x3 external rotation matrix R The output 4x1 external homogenious position vector C Optional 3x3 rotation matrix around x-axis Optional 3x3 rotation matrix around y-axis Optional 3x3 rotation matrix around z-axis

Computes projection matrix decomposition

Deletes moire in given image

Image.

Destroys all the opened HighGUI windows.

Destroys the window with a given name.

Name of the window to be destroyed.

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Source array, real or complex. Destination array of the same size and same type as the source. Transformation flags

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Source array, real or complex. Destination array of the same size and same type as the source. Transformation flags Number of nonzero rows to in the source array (in case of forward 2d transform), or a number of rows of interest in the destination array (in case of inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing them via DFT.

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Source array, real or complex. Destination array of the same size and same type as the source. Transformation flags

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Dilates image by using arbitrary structuring element.

Source image. Destination image.

Dilates image by using arbitrary structuring element.

Source image. Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used.

Dilates image by using arbitrary structuring element.

Source image. Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. Number of times erosion is applied.

Display text on the window's image as an overlay for delay milliseconds. This is not editing the image's data. The text is display on the top of the image.

Name of the window Overlay text to write on the window’s image Delay to display the overlay text. If this function is called before the previous overlay text time out, the timer is restarted and the text updated. . If this value is zero, the text never disapers.

Name of the window Text to write on the window’s statusbar Delay to display the text. If this function is called before the previous text time out, the timer is restarted and the text updated. If this value is zero, the text never disapers.

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Source 8-bit single-channel (binary) image. Output image with calculated distances (32-bit floating-point, single-channel).

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Source 8-bit single-channel (binary) image. Output image with calculated distances (32-bit floating-point, single-channel). Type of distance.

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Source 8-bit single-channel (binary) image. Output image with calculated distances (32-bit floating-point, single-channel). Type of distance. Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask.

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Performs per-element division of two arrays

The first source array. If the pointer is NULL, the array is assumed to be all 1’s. The second source array. The destination array.

Performs per-element division of two arrays

The first source array. If the pointer is NULL, the array is assumed to be all 1’s. The second source array. The destination array. Optional scale factor

Calculates dot product of two arrays in Euclidean metrics

The first source array. The second source array.

Draws the individual chessboard corners detected (as red circles) in case if the board was not found (pattern_was_found=0) or the colored corners connected with lines when the board was found (pattern_was_found≠0).

The destination image; it must be 8-bit color image. The number of inner corners per chessboard row and column. The array of corners detected. Indicates whether the complete board was found (≠0) or not (=0). One may just pass the return value cvFindChessboardCorners here.

Draws contour outlines or interiors in the image

Image where the contours are to be drawn. Like in any other drawing function, the contours are clipped with the ROI. Reference to the first contour. Color of the external contours. Color of internal contours (holes). Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn.

Draws contour outlines or interiors in the image

Calculates absolute difference between two arrays

The first source array. The second source array. The destination array.

Calculates absolute difference between array and scalar

The source array. The destination array.

Calculates absolute difference between array and scalar

The source array. The destination array. The scalar.

Adds frame to accumulator

Input image, 1- or 3-channel, 8-bit or 32-bit floating point. (each channel of multi-channel image is processed independently). Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point.

Adds frame to accumulator

Applies adaptive threshold to array.

Source image. Destination image. Maximum value that is used with Binary and BinaryInv.

Applies adaptive threshold to array.

Source image. Destination image. Maximum value that is used with Binary and BinaryInv. Adaptive thresholding algorithm to use: MeanC or GaussianC.

Applies adaptive threshold to array.

Source image. Destination image. Maximum value that is used with Binary and BinaryInv. Adaptive thresholding algorithm to use: MeanC or GaussianC. Thresholding type.

Applies adaptive threshold to array.

Source image. Destination image. Maximum value that is used with Binary and BinaryInv. Adaptive thresholding algorithm to use: MeanC or GaussianC. Thresholding type. The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, ... The method-dependent parameter. For the methods MeanC and GaussianC it is a constant subtracted from mean or weighted mean (see the discussion), though it may be negative.

Computes per-element sum of two arrays

The first source array. The second source array. The destination array.

Computes per-element sum of two arrays

The first source array. The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Computes sum of array and scalar

The source array. Added scalar. The destination array.

Computes sum of array and scalar

The source array. Added scalar. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Create the font to be used to draw text on an image

Image where the text should be drawn Text to write on the image Point(x,y) where the text should start on the image Font to use to draw the text

Computes weighted sum of two arrays

The first source array. Weight of the first array elements. The second source array. Weight of the second array elements. Scalar, added to each sum. The destination array.

Allocates memory buffer

Buffer size in bytes.

Calculates per-element bit-wise conjunction of two arrays

The first source array. The second source array. The destination array.

Calculates per-element bit-wise conjunction of two arrays

The first source array. The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Calculates per-element bit-wise conjunction of array and scalar

The source array. Scalar to use in the operation. The destination array.

Calculates per-element bit-wise conjunction of array and scalar

The source array. Scalar to use in the operation. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Approximates Freeman chain(s) with polygonal curve

Freeman chain(s) Storage location for the resulting polylines.

Approximates Freeman chain(s) with polygonal curve

Freeman chain(s) Storage location for the resulting polylines. Approximation method. ///

Approximates Freeman chain(s) with polygonal curve

Freeman chain(s) Storage location for the resulting polylines. Approximation method. Method parameter (not used now).

Approximates Freeman chain(s) with polygonal curve

Freeman chain(s) Storage location for the resulting polylines. Approximation method. Method parameter (not used now). Approximates only those contours whose perimeters are not less than minimal_perimeter. Other chains are removed from the resulting structure. If true, the function approximates all chains that access can be obtained to from src_seq by h_next or v_next links. If false, the single chain is approximated.

Approximates polygonal curve(s) with desired precision.

Sequence of array of points. Header size of approximated curve[s]. Container for approximated contours. If it is null, the input sequences' storage is used. Approximation method; only ApproxPolyMethod.DP is supported, that corresponds to Douglas-Peucker algorithm. Method-specific parameter; in case of CV_POLY_APPROX_DP it is a desired approximation accuracy. If case if src_seq is sequence it means whether the single sequence should be approximated or all sequences on the same level or below src_seq (see cvFindContours for description of hierarchical contour structures). And if src_seq is array (CvMat*) of points, the parameter specifies whether the curve is closed (parameter2==true) or not (parameter2==false).

Calculates contour perimeter or curve length

Sequence or array of the curve points.

Calculates contour perimeter or curve length

Sequence or array of the curve points. Starting and ending points of the curve, by default the whole curve length is calculated.

Calculates contour perimeter or curve length

Sequence or array of the curve points. Starting and ending points of the curve, by default the whole curve length is calculated. Indicates whether the curve is closed or not. There are 3 cases: * is_closed=0 - the curve is assumed to be unclosed. * is_closed>0 - the curve is assumed to be closed. * is_closed<0 - if curve is sequence, the flag CV_SEQ_FLAG_CLOSED of ((CvSeq*)curve)->flags is checked to determine if the curve is closed or not, otherwise (curve is represented by array (CvMat*) of points) it is assumed to be unclosed.

initializes CvAttrList structure

array of (attribute_name,attribute_value) pairs

initializes CvAttrList structure

array of (attribute_name,attribute_value) pairs pointer to next chunk of the attributes list

Calculates average (mean) of array elements

The array.

Calculates average (mean) of array elements

The array. The optional operation mask.

Calculates average (mean) of array elements

The array. Pointer to the mean value, may be null if it is not needed. Pointer to the standard deviation.

Calculates average (mean) of array elements

The array. Pointer to the mean value, may be null if it is not needed. Pointer to the standard deviation. The optional operation mask.

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Image to detect objects in. Haar classifier cascade in internal representation. Memory storage to store the resultant sequence of the object candidate rectangles.

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Image to detect objects in. Haar classifier cascade in internal representation. Memory storage to store the resultant sequence of the object candidate rectangles. The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing.

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Finds circles in grayscale image using Hough transform.

The input 8-bit single-channel grayscale image. The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first.

Finds circles in grayscale image using Hough transform.

Finds lines in binary image using Hough transform.

The input 8-bit single-channel binary image. In case of probabilistic method the image is modified by the function. The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. The Hough transform variant. Distance resolution in pixel-related units. Angle resolution measured in radians. Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold.

Finds lines in binary image using Hough transform.

Fills array with random numbers

CvRandState Structure The array to randomize

Fills array with random numbers and updates the RNG state

RNG state initialized by cvRNG. The destination array. Distribution type. The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers.

Initialize CvRandState structure

CvRandState structure to initialize The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. Seed value

Initialize CvRandState structure

Returns 32-bit unsigned integer and updates RNG

RNG state initialized by RandInit and, optionally, customized by RandSetRange (though, the latter function does not affect on the discussed function outcome). uniformly-distributed random 32-bit unsigned integer

Returns floating-point random number and updates RNG

RNG state initialized by cvRNG. uniformly-distributed random floating-point number from 0..1 range (1 is not included).

updates the number of RANSAC iterations

Changes RNG range while preserving RNG state

CvRandState structure to be opdated The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers.

Changes RNG range while preserving RNG state

Randomly shuffles the array elements

The input/output matrix. It is shuffled in-place.

Randomly shuffles the array elements

The input/output matrix. It is shuffled in-place. The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used.

Randomly shuffles the array elements

The input/output matrix. It is shuffled in-place. The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used. The relative parameter that characterizes intensity of the shuffling performed.

Fills matrix with given range of numbers as following: arr(i,j) = (end-start) * (i*cols(arr)+j) / (cols(arr)*rows(arr))

The matrix to initialize. It should be single-channel 32-bit, integer or floating-point. The lower inclusive boundary of the range. The upper exclusive boundary of the range.

Decodes object and returns pointer to it

File storage. The root object node.

Finds object and decodes it

File storage. The parent map. If it is null, the function searches a top-level node. The node name.

Gets next chain point

Chain reader state. Current chain point.

Retrieves integer value from file node

File node. integer that is represented by the file node. If the file node is null, default_value is returned.

Retrieves integer value from file node

File node. The value that is returned if node is null. integer that is represented by the file node. If the file node is null, default_value is returned.

Finds file node and returns its value

File storage. The parent map. If it is null, the function searches a top-level node. The node name.

Finds file node and returns its value

File storage. The parent map. If it is null, the function searches a top-level node. The node name. The value that is returned if the file node is not found.

Reads multiple numbers

File storage. The file node (a sequence) to read numbers from. Reference to the destination array. Specification of each array element. It has the same format as in cvWriteRawData.

Initializes file node sequence reader

File storage. The sequence reader. Initialize it with cvStartReadRawData. The number of elements to read. Destination array. Specification of each array element. It has the same format as in cvWriteRawData.

Retrieves floating-point value from file node

File node. returns floating-point value that is represented by the file node. If the file node is null, default_value is returned.

Retrieves floating-point value from file node

File node. The value that is returned if node is null. returns floating-point value that is represented by the file node. If the file node is null, default_value is returned.

Finds file node and returns its value

File storage. The parent map. If it is null, the function searches a top-level node. The node name.

Finds file node and returns its value

File storage. The parent map. If it is null, the function searches a top-level node. The node name. The value that is returned if the file node is not found.

Retrieves text string from file node

File node. returns text string that is represented by the file node. If the file node is null, default_value is returned.

Retrieves text string from file node

File node. The value that is returned if node is null. returns text string that is represented by the file node. If the file node is null, default_value is returned.

Finds file node and returns its value

File storage. The parent map. If it is null, the function searches a top-level node. The node name.

Finds file node and returns its value

File storage. The parent map. If it is null, the function searches a top-level node. The node name. The value that is returned if the file node is not found.

Initializes val[0] with val0, val[1]...val[3] with zeros

Draws simple, thick or filled rectangle

Image. X-coordinate of the one of the rectangle vertices. Y-coordinate of the one of the rectangle vertices. X-coordinate of the opposite rectangle vertex. Y-coordinate of the opposite rectangle vertex. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Image. One of the rectangle vertices. Opposite rectangle vertex. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Image. One of the rectangle vertices. Opposite rectangle vertex. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Image. Rectangle. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Image. Rectangle. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Image. Rectangle. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. Type of the line, see cvLine description.

Draws simple, thick or filled rectangle

Image. One of the rectangle vertices. Opposite rectangle vertex. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Image. Rectangle. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Image. Rectangle. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Sets a new error handler

The new error_handler Current error handler

Sets a new error handler

The new error_handler Arbitrary pointer that is transparently passed to the error handler Pointer to the previously assigned user data pointer Current error handler

Sets a new error handler

The new error_handler Current error handler

Sets a new error handler

The new error_handler Arbitrary pointer that is transparently passed to the error handler Pointer to the previously assigned user data pointer Current error handler

Reduces matrix to a vector

The input matrix. The output single-row/single-column vector that accumulates somehow all the matrix rows/columns.

Reduces matrix to a vector

The input matrix. The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. The dimension index along which the matrix is reduce. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column. -1 means that the dimension is chosen automatically by analysing the dst size.

Reduces matrix to a vector

Registers new type

Type info structure.

Releases the object

Double pointer to the object.

Releases the object

Double pointer to the object.

Deallocates BGCodeBookModel structure

Structure to be released.

Releases the CvCapture structure allocated by cvCreateFileCapture or cvCreateCameraCapture.

Reference to video capturing structure.

Deallocates ConDensation filter structure

Structure to be released.

Releases array data.

Array header.

Destroys a tree of feature vectors

pointer to tree being destroyed.

Releases file storage

Reference to the released file storage.

Finishes graph traversal procedure

Reference to graph traverser.

Releases haar classifier cascade

Double pointer to the released cascade.

Releases the histogram (header and the data).

Double pointer to the released histogram.

Releases header and image data

Reference to the header of the deallocated image.

Releases IplImage header

Reference to the deallocated header.

Deallocates Kalman filter structure

Kalman filter structure.

release memory allocated for CvLatentSvmDetector structure

Free the given LSH structure.

Deallocates matrix.

Reference to the matrix.

Deallocates multi-dimensional array

Reference to the array.

Releases memory storage

Pointer to the released storage.

Deallocates 3D object structure

Reference to CvPOSIT structure.

Releases pyramid

Deallocates sparse array

Reference to the array.

Releases block matching stereo correspondence structure

Reference to the released structure

Releases the state structure of the graph cut-based stereo correspondence algorithm

Reference to the released structure

Releases the structure IplConvKernel that is no longer needed. If *element is NULL, the function has no effect.

Pointer to the deleted structuring element.

Finishes writing to video file and releases the structure.

Reference to video file writer structure.

Applies generic geometrical transformation to the image.

Source image. Destination image. The map of x-coordinates (32fC1 image). The map of y-coordinates (32fC1 image).

Applies generic geometrical transformation to the image.

Source image. Destination image. The map of x-coordinates (32fC1 image). The map of y-coordinates (32fC1 image). A combination of interpolation method and the optional flag(s).

Applies generic geometrical transformation to the image.

Source image. Destination image. The map of x-coordinates (32fC1 image). The map of y-coordinates (32fC1 image). A combination of interpolation method and the optional flag(s). A value used to fill outliers.

Removes node from tree

The removed node. The top level node. If node->v_prev = null and node->h_prev is null (i.e. if node is the first child of frame), frame->v_next is set to node->h_next (i.e. the first child or frame is changed).

Fill destination array with tiled source array

Source array, image or matrix. Destination array, image or matrix.

Reprojects disparity image to 3D space

Disparity map. 3-channel, 16-bit integer or 32-bit floating-point image - the output map of 3D points. The reprojection 4x4 matrix.

Releases image ROI. After that the whole image is considered selected.

Image header.

Changes shape of matrix/image without copying data

Input array. Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged.

Changes shape of matrix/image without copying data

Input array. Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged. New number of rows. new_rows = 0 means that number of rows remains unchanged unless it needs to be changed according to new_cn value. destination array to be changed.

Changes shape of matrix/image without copying data

Input array. Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged.

Changes shape of matrix/image without copying data

Changes shape of multi-dimensional array w/o copying data

Input array. Size of output header to distinguish between IplImage, CvMat and CvMatND output headers. Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged. New number of dimensions. new_dims = 0 means that number of dimensions remains the same. Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used

Changes shape of multi-dimensional array w/o copying data

Input array. Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged. New number of dimensions. new_dims = 0 means that number of dimensions remains the same. Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used

Resizes image src so that it fits exactly to dst. If ROI is set, the function consideres the ROI as supported as usual.

Source image. Destination image.

Resizes image src so that it fits exactly to dst. If ROI is set, the function consideres the ROI as supported as usual.

Source image. Destination image. Interpolation method.

Changes size of the window.

Name of the window to be resized. New width. New height.

Restores memory storage position

Memory storage New storage top position

Returns the pointer to the image grabbed with cvGrabFrame function. The returned image should not be released or modified by user.

video capturing structure.

Returns the pointer to the image grabbed with cvGrabFrame function. The returned image should not be released or modified by user.

video capturing structure. non-zero streamIdx is only valid for multi-head camera live streams

Returns the pointer to the image grabbed with cvGrabFrame function. The returned image should not be released or modified by user.

video capturing structure. non-zero streamIdx is only valid for multi-head camera live streams

Initializes random number generator state

64-bit value used to initiate a random sequence.

Converts rotation matrix to rotation vector or vice versa

The input rotation vector (3x1 or 1x3) or rotation matrix (3x3). The output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively.

Converts rotation matrix to rotation vector or vice versa

The input rotation vector (3x1 or 1x3) or rotation matrix (3x3). The output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. Optional output Jacobian matrix, 3x9 or 9x3 - partial derivatives of the output array components w.r.t the input array components.

Returns the nearest integer value to the argument.

The input floating-point value

Computes RQ decomposition for 3x3 matrices

The 3x3 input matrix M The output 3x3 upper-triangular matrix R The output 3x3 orthogonal matrix Q

Computes RQ decomposition for 3x3 matrices

The 3x3 input matrix M The output 3x3 upper-triangular matrix R The output 3x3 orthogonal matrix Q Optional 3x3 rotation matrix around x-axis Optional 3x3 rotation matrix around y-axis Optional 3x3 rotation matrix around z-axis

Computes RQ decomposition for 3x3 matrices

Runs cascade of boosted classifier at given image location

Haar classifier cascade. Top-left corner of the analyzed region. Size of the region is a original window size scaled by the currenly set scale. The current window size may be retrieved using cvGetHaarClassifierCascadeWindowSize function. positive value if the analyzed rectangle passed all the classifier stages (it is a candidate) and zero or negative value otherwise.

Runs cascade of boosted classifier at given image location

Haar classifier cascade. Top-left corner of the analyzed region. Size of the region is a original window size scaled by the currenly set scale. The current window size may be retrieved using cvGetHaarClassifierCascadeWindowSize function. Initial zero-based index of the cascade stage to start from. The function assumes that all the previous stages are passed. This feature is used internally by cvHaarDetectObjects for better processor cache utilization. positive value if the analyzed rectangle passed all the classifier stages (it is a candidate) and zero or negative value otherwise.

Calculates weighted sum of input image image and the accumulator acc so that acc becomes a running average of frame sequence: acc(x,y)=(1-α)•acc(x,y) + α•image(x,y) if mask(x,y)!=null

References the specified object, which makes it ineligible for garbage collection from the start of the current routine to the point where this method is called.

Returns obj.CvPtr if obj != null; otherwise, IntPtr.Zero

Converts IEnumerable to Array

CV_AA

CV_AUTOSTEP

CV_FILLED

CV_LOG2

CV_PI

CV_WHOLE_SEQ_END_INDEX

CV_WHOLE_SEQ

if set, the difference between the current pixel and seed pixel is considered, otherwise the difference between neighbor pixels is considered (the range is floating)

if set, the function does not fill the image (new_val is ignored), but fills the mask (that must be non-null in this case)

4つの文字からFOURCCの整数値を得る

CV_NODE_IDX

CV_NODE_VAL

Constructs a color value

Error Handler

The numeric code for error status The source file name where error is encountered A description of the error The source file name where error is encountered The line number in the souce where error is encountered Pointer to the user data. Ignored by the standard handlers

Read callback function

Pointer to the function to be called every time the button changed its state.

IEnumerable<T> extension methods for .NET Framework 2.0

Enumerable.Select

Enumerable.Select -> ToArray

Enumerable.Where

Enumerable.Where -> ToArray

Enumerable.ToArray

Enumerable.Any

Enumerable.All

Enumerable.Count

Input/output flags for Eigen Objects (PCA) Functions

[CV_EIGOBJ_NO_CALLBACK]

[CV_EIGOBJ_INPUT_CALLBACK]

[CV_EIGOBJ_OUTPUT_CALLBACK]

[CV_EIGOBJ_BOTH_CALLBACK]

[CV_CPU_NONE]

[CV_CPU_MMX]

[CV_CPU_SSE]

[CV_CPU_SSE2]

[CV_CPU_SSE3]

[CV_CPU_SSSE3]

[CV_CPU_SSE4_1]

[CV_CPU_SSE4_2]

[CV_CPU_POPCNT]

[CV_CPU_AVX]

[CV_HARDWARE_MAX_FEATURE]

Miscellaneous flags for cvKMeans2

[= 0]

[KMEANS_RANDOM_CENTERS]

[KMEANS_PP_CENTERS]

[KMEANS_USE_INITIAL_LABELS]

Various operation flags for cvFindDominantPoints

[CV_DOMINANT_IPAN]

Marker styles for CvArr.DrawMarker

A circle polyline

A filled circle

A cross

A tilted cross

A circle and a cross

A circle and a tilted cross

A diamond polyline

A filled diamond

A square polyline

A filledsquare

The format type IDs for cv::imwrite and cv::inencode

In the case of JPEG it can be a quality, from 0 to 100 (the higher is the better), 95 by default. [CV_IMWRITE_JPEG_QUALITY]

In the case of PNG it can be the compression level, from 0 to 9 (the higher value means smaller size and longer compression time), 3 by default. [CV_IMWRITE_PNG_COMPRESSION]

In the case of PPM, PGM or PBM it can a binary format flag, 0 or 1, 1 by default. [CV_IMWRITE_PXM_BINARY]

Property identifiers for cvGetWindowProperty/cvSetWindowProperty

Normal mode [CV_WND_PROP_AUTOSIZE]

Fullscreen [CV_WND_PROP_FULLSCREEN]

[CV_WND_PROP_ASPECTRATIO]

opengl support [CV_WND_PROP_OPENGL]

New value of the window property.

Change the window to normal size or make the window resizable. [CV_WINDOW_NORMAL]

Constrain the size by the displayed image. The window is not resizable. [CV_WINDOW_AUTOSIZE]

Change the window to fullscreen. [CV_WINDOW_FULLSCREEN]

Make the window resizable without any ratio constraints. [CV_WINDOW_FREERATIO]

Make the window resizable, but preserve the proportions of the displayed image. [CV_WINDOW_KEEPRATIO]

CV_FACE_ELEMENTS

[CV_FACE_MOUTH]

[CV_FACE_LEFT_EYE]

[CV_FACE_RIGHT_EYE]

The operation flags for cvFontQt

QFont::Light

QFont::Normal

QFont::DemiBold

QFont::Bold

QFont::Black

The operation flags for cvFontQt

QFont::StyleNormal

QFont::StyleItalic

QFont::StyleOblique

Button type flags (cvCreateButton)

The button will be a push button. [CV_PUSH_BUTTON]

The button will be a checkbox button. [CV_CHECKBOX]

The button will be a radiobox button. The radiobox on the same buttonbar (same line) are exclusive; one on can be select at the time. [CV_RADIOBOX]

channel indices for multi-head camera live streams

Depth values in mm (CV_16UC1) [CV_CAP_OPENNI_DEPTH_MAP]

XYZ in meters (CV_32FC3) [CV_CAP_OPENNI_POINT_CLOUD_MAP]

Disparity in pixels (CV_8UC1) [CV_CAP_OPENNI_DISPARITY_MAP]

Disparity in pixels (CV_32FC1) [CV_CAP_OPENNI_DISPARITY_MAP_32F]

CV_8UC1 [CV_CAP_OPENNI_VALID_DEPTH_MASK]

[CV_CAP_OPENNI_BGR_IMAGE]

[CV_CAP_OPENNI_GRAY_IMAGE]

[CV_CAP_OPENNI_VGA_30HZ]

[CV_CAP_OPENNI_SXGA_15HZ]

BGR [CV_CAP_ANDROID_COLOR_FRAME_BGR]

[CV_CAP_ANDROID_COLOR_FRAME]

Y [CV_CAP_ANDROID_GREY_FRAME]

[CV_CAP_ANDROID_COLOR_FRAME_RGB]

[CV_CAP_ANDROID_COLOR_FRAME_BGRA]

[CV_CAP_ANDROID_COLOR_FRAME_RGBA]

[CV_DIST_LABEL_CCOMP]

[CV_DIST_LABEL_PIXEL]

floodFill Operation flags. Lower bits contain a connectivity value, 4 (default) or 8, used within the function. Connectivity determines which neighbors of a pixel are considered. Upper bits can be 0 or a combination of the following flags:

4-connected line. [= 4]

8-connected line. [= 8]

If set, the difference between the current pixel and seed pixel is considered. Otherwise, the difference between neighbor pixels is considered (that is, the range is floating). [CV_FLOODFILL_FIXED_RANGE]

If set, the function does not change the image ( newVal is ignored), but fills the mask. The flag can be used for the second variant only. [CV_FLOODFILL_MASK_ONLY]

Button that is used on Qt Window

Track whether Dispose has been called

Constructor

Name of the button ( if null, the name will be “button <number of boutton>”)

Constructor

Name of the button ( if null, the name will be “button <number of boutton>”) Pointer to the function to be called every time the button changed its state.

Constructor

Name of the button ( if null, the name will be “button <number of boutton>”) Pointer to the function to be called every time the button changed its state. object passed to the callback function.

Constructor

Clean up any resources being used.

Name of this trackbar

Gets the callback delegate which occurs when the Value property of a track bar changes, either by movement of the scroll box or by manipulation in code.

All created buttons

The format-specific save parameters for cv::imwrite and cv::imencode

format type ID

value of parameter

Constructor

format type ID value of parameter

The format-specific save parameters for cv::imwrite and cv::imencode

Constructor

value of parameter, from 0 to 100 (the higher is the better), 95 by default.

The format-specific save parameters for cv::imwrite and cv::imencode

Constructor

value of parameter, from 0 to 9 (the higher value means smaller size and longer compression time), 3 by default.

The format-specific save parameters for cv::imwrite and cv::imencode

Constructor

value of parameter. binary format flag, 0 or 1, 1 by default.

Checks whether PInvoke functions can be called

DllImportの際にDllNotFoundExceptionかBadImageFormatExceptionが発生した際に呼び出されるメソッド。エラーメッセージを表示して解決策をユーザに示す。

Class to get address of string array

Class to get address of specified jagged array

Name of library to be loaded

Name of function to be called

Pointer which retrieved by LoadLibrary

Pointer which retrieved by GetProcAddress

Delegate which is converted from function pointer

Constructor

Name of library Name of function

Releases resources

Provides information for the platform which the user is using

OS type

Runtime type

Substitute of System.Action

Class that converts structure into pointer and cleans up resources automatically

Pointer

Structure

Size of allocated memory

Clean up resources to be used

Class that converts structure into pointer and cleans up resources automatically (generic version)

Original GCHandle that implement IDisposable

Destructor

IEnumerable<T>.ToArray of LINQ

OpenCV Constants defined by macro

Arbitrary array

Calculates absolute difference between two arrays

The second source array. The destination array.

Calculates absolute difference between array and scalar

The destination array.

Calculates absolute difference between array and scalar

The destination array. The scalar.

Adds frame to accumulator

Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point.

Adds frame to accumulator

Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. Optional operation mask.

Applies adaptive threshold to array.

Destination image. Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV.

Applies adaptive threshold to array.

Destination image. Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or CV_ADAPTIVE_THRESH_GAUSSIAN_C.

Applies adaptive threshold to array.

Destination image. Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or CV_ADAPTIVE_THRESH_GAUSSIAN_C. Thresholding type. The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, ... The method-dependent parameter. For the methods CV_ADAPTIVE_THRESH_MEAN_C and CV_ADAPTIVE_THRESH_GAUSSIAN_C it is a constant subtracted from mean or weighted mean (see the discussion), though it may be negative.

Computes per-element sum of two arrays

The second source array. The destination array.

Computes per-element sum of two arrays

The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Computes sum of array and scalar

Added scalar. The destination array.

Computes sum of array and scalar

Added scalar. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Create the font to be used to draw text on an image

Text to write on the image Point(x,y) where the text should start on the image Font to use to draw the text

Computes weighted sum of two arrays

Weight of the first array elements. The second source array. Weight of the second array elements. Scalar, added to each sum. The destination array.

Calculates per-element bit-wise conjunction of two arrays

The second source array. The destination array.

Calculates per-element bit-wise conjunction of two arrays

The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Calculates per-element bit-wise conjunction of array and scalar

Scalar to use in the operation. The destination array.

Calculates per-element bit-wise conjunction of array and scalar

Scalar to use in the operation. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Calculates contour perimeter or curve length

Starting and ending points of the curve, by default the whole curve length is calculated.

Calculates contour perimeter or curve length

Starting and ending points of the curve, by default the whole curve length is calculated. Indicates whether the curve is closed or not. There are 3 cases: * is_closed=0 - the curve is assumed to be unclosed. * is_closed>0 - the curve is assumed to be closed. * is_closed<0 - if curve is sequence, the flag CV_SEQ_FLAG_CLOSED of ((CvSeq*)curve)->flags is checked to determine if the curve is closed or not, otherwise (curve is represented by array (CvMat*) of points) it is assumed to be unclosed.

Calculates average (mean) of array elements

The optional operation mask.

Calculates average (mean) of array elements

Pointer to the mean value, may be null if it is not needed. Pointer to the standard deviation.

Calculates average (mean) of array elements

Pointer to the mean value, may be null if it is not needed. Pointer to the standard deviation. The optional operation mask.

Calculates up-right bounding rectangle of point set.

The update flag. Here is list of possible combination of the flag values and type of contour: * points is CvContour*, update=0: the bounding rectangle is not calculated, but it is read from rect field of the contour header. * points is CvContour*, update=1: the bounding rectangle is calculated and written to rect field of the contour header. For example, this mode is used by cvFindContours. * points is CvSeq* or CvMat*: update is ignored, the bounding rectangle is calculated and returned.

Image to store the edges found by the function. The first threshold. The second threshold.

Image to store the edges found by the function. The first threshold. The second threshold. Aperture parameter for Sobel operator.

Checks every element of input array for invalid values

returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The operation flags returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The operation flags The inclusive lower boundary of valid values range. It is used only if CV_CHECK_RANGE is set. The exclusive upper boundary of valid values range. It is used only if CV_CHECK_RANGE is set. returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

The operation flags returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise.

Checks every element of input array for invalid values

Tests contour convexity.

Draws a circle

X-coordinate of the center of the circle. Y-coordinate of the center of the circle. Radius of the circle. Circle color.

Draws a circle

X-coordinate of the center of the circle. Y-coordinate of the center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. Type of the circle boundary.

Draws a circle

Center of the circle. Radius of the circle. Circle color.

Draws a circle

Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn.

Draws a circle

Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. Type of the circle boundary.

Draws a circle

Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. Type of the circle boundary. Number of fractional bits in the center coordinates and radius value.

Draws a circle

X-coordinate of the center of the circle. Y-coordinate of the center of the circle. Radius of the circle. Circle color.

Draws a circle

Center of the circle. Radius of the circle. Circle color.

Draws a circle

Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn.

Draws a circle

Center of the circle. Radius of the circle. Circle color. Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. Type of the circle boundary.

Draws a circle

Clears the particular array element

Array of the element indices

Performs per-element comparison of two arrays

The second source array. Both source array must have a single channel. The destination array, must have 8u or 8s type. The flag specifying the relation between the elements to be checked

Performs per-element comparison of array and scalar

The scalar value to compare each array element with. The destination array, must have 8u or 8s type. The flag specifying the relation between the elements to be checked

Calculates area of the whole contour or contour section.

Starting and ending points of the contour section of interest, by default area of the whole contour is calculated.

Alias for cvArcLength(curve,Whole_Seq,1)

Converts one array to another with optional linear transformation

Destination array.

Converts one array to another with optional linear transformation

Destination array. Scale factor.

Converts one array to another with optional linear transformation

Destination array. Scale factor. Value added to the scaled source array elements.

Converts one array to another with optional linear transformation

Destination array.

Converts one array to another with optional linear transformation

Destination array. Scale factor.

Converts one array to another with optional linear transformation

Destination array. Scale factor. Value added to the scaled source array elements.

Converts one array to another with optional linear transformation

Destination array.

Converts one array to another with optional linear transformation

Destination array. Scale factor.

Converts one array to another with optional linear transformation

Destination array. Scale factor. Value added to the scaled source array elements.

Converts one array to another with optional linear transformation

Destination array.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Destination array (should have 8u depth).

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Destination array (should have 8u depth). ScaleAbs factor.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Destination array (should have 8u depth). ScaleAbs factor. Value added to the scaled source array elements.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Destination array (should have 8u depth).

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Destination array (should have 8u depth). ScaleAbs factor.

Converts input array elements to 8-bit unsigned integer another with optional linear transformation

Destination array (should have 8u depth). ScaleAbs factor. Value added to the scaled source array elements.

Finds convex hull of point set

Vector of 0-based point indices of the hull points in the original array. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

The output convex hull. It is either a vector of points that form the hull. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convex hull of point set

The output convex hull. It is either a vector of points that form the hull. Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE.

Finds convexity defects of contour

Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0.

Finds convexity defects of contour

Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0. Container for output sequence of convexity defects. If it is null, contour or hull (in that order) storage is used.

Finds convexity defects of contour

Convex hull obtained using cvConvexHull2 that should contain indices to the contour points

Copies one array to another

The destination array.

Copies one array to another

The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Copies image and makes border around it.

The destination image. Coordinates of the top-left corner (or bottom-left in case of images with bottom-left origin) of the destination image rectangle where the source image (or its ROI) is copied. Size of the rectanlge matches the source image size/ROI size. Type of the border to create around the copied source image rectangle.

Copies image and makes border around it.

Calculates eigenvalues and eigenvectors of image blocks for corner detection

Image to store the results. It must be 6 times wider than the input image. Neighborhood size.

Calculates eigenvalues and eigenvectors of image blocks for corner detection

Image to store the results. It must be 6 times wider than the input image. Neighborhood size. Aperture parameter for Sobel operator

Image to store the Harris detector responces. Should have the same size as image. Neighborhood size.

Image to store the Harris detector responces. Should have the same size as image. Neighborhood size. Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing.

Calculates minimal eigenvalue of gradient matrices for corner detection

Image to store the minimal eigen values. Should have the same size as image Neighborhood size.

Calculates minimal eigenvalue of gradient matrices for corner detection

Image to store the minimal eigen values. Should have the same size as image Neighborhood size. Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing.

Counts non-zero array elements

the number of non-zero elements in arr

Allocates array data.

Builds pyramid for an image

Calculates cross product of two 3D vectors

The second source vector. The destination vector.

Converts image from one color space to another.

The destination image of the same data type as the source one. The number of channels may be different. Color conversion operation that can be specifed using CV_<src_color_space>2<dst_color_space> constants (see below).

Performs forward or inverse Discrete Cosine transform of 1D or 2D floating-point array

Destination array of the same size and same type as the source. Transformation flags.

Decrements array data reference counter．

Returns determinant of matrix

determinant of the square matrix mat

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Destination array of the same size and same type as the source. Transformation flags

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Destination array of the same size and same type as the source. Transformation flags Number of nonzero rows to in the source array (in case of forward 2d transform), or a number of rows of interest in the destination array (in case of inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing them via DFT.

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Destination array of the same size and same type as the source. Transformation flags

Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array

Dilates image by using arbitrary structuring element.

Destination image.

Dilates image by using arbitrary structuring element.

Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used.

Dilates image by using arbitrary structuring element.

Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. Number of times erosion is applied.

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Output image with calculated distances (32-bit floating-point, single-channel).

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Output image with calculated distances (32-bit floating-point, single-channel). Type of distance.

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Output image with calculated distances (32-bit floating-point, single-channel). Type of distance. Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask.

Calculates distance to closest zero pixel for all non-zero pixels of source image.

Performs per-element division of two arrays

The second source array. The destination array.

Performs per-element division of two arrays

The second source array. The destination array. Optional scale factor

The number of inner corners per chessboard row and column. The array of corners detected. Indicates whether the complete board was found (≠0) or not (=0). One may just pass the return value cvFindChessboardCorners here.

Draws contour outlines or interiors in the image

Reference to the first contour. Color of the external contours. Color of internal contours (holes). Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn.

Draws contour outlines or interiors in the image

Computes eigenvalues and eigenvectors of symmetric matrix

The output matrix of eigenvectors, stored as a subsequent rows. The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course).

Computes eigenvalues and eigenvectors of symmetric matrix

The output matrix of eigenvectors, stored as a subsequent rows. The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). Accuracy of diagonalization (typically, DBL_EPSILON=≈10-15 is enough).

Draws simple or thick elliptic arc or fills ellipse sector

Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color.

Draws simple or thick elliptic arc or fills ellipse sector

Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color. Thickness of the ellipse arc.

Draws simple or thick elliptic arc or fills ellipse sector

Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color. Thickness of the ellipse arc. Type of the ellipse boundary.

Draws simple or thick elliptic arc or fills ellipse sector

Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color.

Draws simple or thick elliptic arc or fills ellipse sector

Center of the ellipse. Length of the ellipse axes. Rotation angle. Starting angle of the elliptic arc. Ending angle of the elliptic arc. Ellipse color. Thickness of the ellipse arc.

Draws simple or thick elliptic arc or fills ellipse sector

The enclosing box of the ellipse drawn Ellipse color.

Draws simple or thick elliptic arc or fills ellipse sector

The enclosing box of the ellipse drawn Ellipse color. Thickness of the ellipse boundary.

Draws simple or thick elliptic arc or fills ellipse sector

The enclosing box of the ellipse drawn Ellipse color. Thickness of the ellipse boundary. Type of the ellipse boundary

Draws simple or thick elliptic arc or fills ellipse sector

The enclosing box of the ellipse drawn Ellipse color. Thickness of the ellipse boundary. Type of the ellipse boundary Number of fractional bits in the box vertex coordinates.

Equalizes histogram of grayscale image.

The output image of the same size and the same data type as src.

Erodes image by using arbitrary structuring element.

Destination image.

Erodes image by using arbitrary structuring element.

Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used.

Erodes image by using arbitrary structuring element.

Destination image. Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. Number of times erosion is applied.

Calculates exponent of every array element

The destination array, it should have double type or the same type as the source.

Extracts the contours of Maximally Stable Extremal Regions

Extracts Speeded Up Robust Features from image

The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. Memory storage where keypoints and descriptors will be stored. Various algorithm parameters put to the structure CvSURFParams

Extracts Speeded Up Robust Features from image

The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. Various algorithm parameters put to the structure CvSURFParams

Extracts Speeded Up Robust Features from image

The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. Various algorithm parameters put to the structure CvSURFParams If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint).

Fills convex polygon

Array of pointers to a single polygon. Polygon color.

Fills convex polygon

Array of pointers to a single polygon. Polygon color. Type of the polygon boundaries.

Fills convex polygon

Array of pointers to a single polygon. Polygon color. Type of the polygon boundaries. Number of fractional bits in the vertex coordinates.

Fills polygons interior

Array of pointers to polygons. Polygon color.

Fills polygons interior

Array of pointers to polygons. Polygon color. ype of the polygon boundaries.

Fills polygons interior

Array of pointers to polygons. Polygon color. ype of the polygon boundaries. Number of fractional bits in the vertex coordinates.

The destination image. Convolution kernel, single-channel floating point matrix. If you want to apply different kernels to different channels, split the image using cvSplit into separate color planes and process them individually. The anchor of the kernel that indicates the relative position of a filtered point within the kernel. The anchor shoud lie within the kernel. The special default value (-1,-1) means that it is at the kernel center.

Finds positions of internal corners of the chessboard

The number of inner corners per chessboard row and column. The output array of corners detected. returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false.

Finds positions of internal corners of the chessboard

The number of inner corners per chessboard row and column. The output array of corners detected. The output corner counter. If it is not null, the function stores there the number of corners found. returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false.

Finds positions of internal corners of the chessboard

The number of inner corners per chessboard row and column. The output array of corners detected. The output corner counter. If it is not null, the function stores there the number of corners found. Various operation flags returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false.

Retrieves contours from the binary image and returns the number of retrieved contours.

Container of the retrieved contours. Output parameter, will contain the pointer to the first outer contour. The number of retrieved contours.

Retrieves contours from the binary image and returns the number of retrieved contours.

Container of the retrieved contours. Output parameter, will contain the pointer to the first outer contour. Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. Retrieval mode. Approximation method. Offset, by which every contour point is shifted. This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. The number of retrieved contours.

Iterates to find the sub-pixel accurate location of corners, or radial saddle points.

Initial coordinates of the input corners and refined coordinates on output. Number of corners. Half sizes of the search window. Half size of the dead region in the middle of the search zone over which the summation in formulae below is not done. It is used sometimes to avoid possible singularities of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such size. Criteria for termination of the iterative process of corner refinement. That is, the process of corner position refinement stops either after certain number of iteration or when a required accuracy is achieved. The criteria may specify either of or both the maximum number of iteration and the required accuracy.

Fits ellipse to set of 2D points

ellipse that fits best (in least-squares sense) to a set of 2D points.

Fits line to 2D or 3D point set

The distance used for fitting (see the discussion). Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. The output line parameters. In case of 2d fitting it is array of 4 floats (vx, vy, x0, y0) where (vx, vy) is a normalized vector collinear to the line and (x0, y0) is some point on the line. In case of 3D fitting it is array of 6 floats (vx, vy, vz, x0, y0, z0) where (vx, vy, vz) is a normalized vector collinear to the line and (x0, y0, z0) is some point on the line.

Flip a 2D array around vertical, horizontal or both axises

Destination array. If dst = null the flipping is done in-place.

Flip a 2D array around vertical, horizontal or both axises

Destination array. If dst = null the flipping is done in-place. Specifies how to flip the array.

Flip a 2D array around vertical, horizontal or both axises

Destination array. If dst = null the flipping is done in-place.

Flip a 2D array around vertical, horizontal or both axises

Destination array. If dst = null the flipping is done in-place. Specifies how to flip the array.

Fills a connected component with given color.

The starting point. New value of repainted domain pixels.

Fills a connected component with given color.

The starting point. New value of repainted domain pixels. Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. Pointer to structure the function fills with the information about the repainted domain.

Fills a connected component with given color.

Return the particular array element

The first zero-based component of the element index

Return the particular array element

The first zero-based component of the element index The second zero-based component of the element index

Return the particular array element

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index

Return the particular array element

Array of the element indices the particular array element

Returns array column

Zero-based index of the selected column.

Returns array column span

Zero-based index of the starting column (inclusive) of the span. Zero-based index of the ending column (exclusive) of the span.

Returns one of array diagonals

Reference to the resulting sub-array header.

Returns one of array diagonals

Reference to the resulting sub-array header. Array diagonal. Zero corresponds to the main diagonal, -1 corresponds to the diagonal above the main etc., 1 corresponds to the diagonal below the main etc.

Return number of array dimensions and their sizes

number of array dimensions.

Return number of array dimensions and their sizes

Optional output vector of the array dimension sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next. number of array dimensions.

Return the size of particular dimension

Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width). the particular dimension size (number of elements per that dimension).

Returns type of array elements

type of the array elements

Retrieves pixel quadrangle from image with sub-pixel accuracy.

Extracted quadrangle. The transformation 2 × 3 matrix [A|b].

Retrieves low-level information about the array

Output pointer to the whole image origin or ROI origin if ROI is set.

Retrieves low-level information about the array

Output pointer to the whole image origin or ROI origin if ROI is set. Output full row length in bytes.

Retrieves low-level information about the array

Output pointer to the whole image origin or ROI origin if ROI is set. Output full row length in bytes. Output ROI size.

Return the particular element of single-channel array

The first zero-based component of the element index the particular element of single-channel array.

Return the particular element of single-channel array

The first zero-based component of the element index The second zero-based component of the element index the particular element of single-channel array.

Return the particular element of single-channel array

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index the particular element of single-channel array.

Return the particular element of single-channel array

Array of the element indices the particular element of single-channel array.

Retrieves pixel rectangle from image with sub-pixel accuracy.

Extracted rectangle. Floating point coordinates of the extracted rectangle center within the source image. The center must be inside the image.

Returns array row

Zero-based index of the selected row.

Returns array row span

Zero-based index of the starting row (inclusive) of the span. Zero-based index of the ending row (exclusive) of the span.

Returns array row span

Zero-based index of the starting row (inclusive) of the span. Zero-based index of the ending row (exclusive) of the span. Index step in the row span. That is, the function extracts every delta_row-th row from start_row and up to (but not including) end_row.

Returns size of matrix or image ROI

Retrieves keypoints using the StarDetector algorithm.

Memory storage where the keypoints will be stored

Retrieves keypoints using the StarDetector algorithm.

Memory storage where the keypoints will be stored Various algorithm parameters given to the structure CvStarDetectorParams

Returns matrix header corresponding to the rectangular sub-array of input image or matrix

Reference to the resultant sub-array header. Zero-based coordinates of the rectangle of interest. Reference to the header, corresponding to a specified rectangle of the input array.

Returns matrix header corresponding to the rectangular sub-array of input image or matrix

Reference to the resultant sub-array header. Zero-based coordinates of the rectangle of interest. Reference to the header, corresponding to a specified rectangle of the input array.

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Haar classifier cascade in internal representation. Memory storage to store the resultant sequence of the object candidate rectangles.

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Haar classifier cascade in internal representation. Memory storage to store the resultant sequence of the object candidate rectangles. The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing.

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Finds circles in grayscale image using Hough transform.

The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first.

Finds circles in grayscale image using Hough transform.

Finds lines in binary image using Hough transform.

The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. The Hough transform variant. Distance resolution in pixel-related units. Angle resolution measured in radians. Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold.

Finds lines in binary image using Hough transform.

Increments array data reference counter

The function cvIncRefData increments CvMat or CvMatND data reference counter and returns the new counter value if the reference counter pointer is not NULL, otherwise it returns zero.

Inpaints the selected region in the image.

The inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted. The output image of the same format and the same size as input. The radius of circlular neighborhood of each point inpainted that is considered by the algorithm. The inpainting method.

Checks that array elements lie between elements of two other arrays

The inclusive lower boundary array. The exclusive upper boundary array. The destination array, must have 8u or 8s type.

Checks that array elements lie between two scalars

The inclusive lower boundary. The exclusive upper boundary. The destination array, must have 8u or 8s type.

Calculates integral images.

The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f).

Calculates integral images.

The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f).

Calculates integral images.

The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f). The integral for the image rotated by 45 degrees, W+1xH+1, the same data type as sum.

Finds inverse or pseudo-inverse of matrix

The destination matrix. In case of LU method the function returns src1 determinant (src1 must be square). If it is 0, the matrix is not inverted and src2 is filled with zeros. In case of SVD methods the function returns the inverted condition number of src1

Finds inverse or pseudo-inverse of matrix

The destination matrix. Inversion method In case of LU method the function returns src1 determinant (src1 must be square). If it is 0, the matrix is not inverted and src2 is filled with zeros. In case of SVD methods the function returns the inverted condition number of src1

Finds inverse or pseudo-inverse of matrix

Splits set of vectors by given number of clusters

Number of clusters to split the set by. Output integer vector storing cluster indices for every sample. Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations).

Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator.

Destination image.

Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator.

Destination image. Aperture size (it has the same meaning as in cvSobel).

Draws a line segment connecting two points

First point's x-coordinate of the line segment. First point's y-coordinate of the line segment. Second point's x-coordinate of the line segment. Second point's y-coordinate of the line segment. Line color.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color. Line thickness.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line. Number of fractional bits in the point coordinates.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color. Line thickness.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line.

Draws a line segment connecting two points

First point of the line segment. Second point of the line segment. Line color. Line thickness. Type of the line. Number of fractional bits in the point coordinates.

Performs forward or inverse linear-polar image transform

Calculates natural logarithm of every array element absolute value

The destination array, it should have double type or the same type as the source.

Remaps image to log-polar space. The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc.

Destination image. The transformation center, where the output precision is maximal. Magnitude scale parameter. See below.

Remaps image to log-polar space. The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc.

Destination image. The transformation center, where the output precision is maximal. Magnitude scale parameter. See below. A combination of interpolation method and the optional flags.

Performs look-up table transform of array

Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array. In case of multi-channel source and destination arrays, the table should either have a single-channel (in this case the same table is used for all channels), or the same number of channels as the source/destination array.

Performs look-up table transform of array

Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array.

Performs look-up table transform of array

Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array.

Performs look-up table transform of array

Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array.

Performs look-up table transform of array

Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array.

Performs look-up table transform of array

Destination array of arbitrary depth and of the same number of channels as the source array. Look-up table of 256 elements; should have the same depth as the destination array.

Compares template against overlapped image regions.

Searched template; must be not greater than the source image and the same data type as the image. A map of comparison results; single-channel 32-bit floating-point. If image is W×H and templ is w×h then result must be W-w+1×H-h+1. Specifies the way the template must be compared with image regions.

Finds per-element maximum of two arrays

The second source array. The destination array.

Finds per-element maximum of array and scalar

The scalar value. The destination array.

Finds per-element minimum of two arrays

The second source array. The destination array.

Finds circumscribed rectangle of minimal area for given 2D point set

The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull.

Finds circumscribed rectangle of minimal area for given 2D point set

The point tested against the contour. The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull.

Finds circumscribed rectangle of minimal area for given 2D point set

Output parameter. The center of the enclosing circle. Output parameter. The radius of the enclosing circle. The function cvMinEnclosingCircle finds the minimal circumscribed circle for 2D point set using iterative algorithm. It returns true if the resultant circle contains all the input points and false otherwise (i.e. algorithm failed).

Finds global minimum and maximum in array or subarray

Pointer to returned minimum value. Pointer to returned maximum value.

Finds global minimum and maximum in array or subarray

Pointer to returned minimum value. Pointer to returned maximum value. The optional mask that is used to select a subarray.

Finds global minimum and maximum in array or subarray

Pointer to returned minimum location. Pointer to returned maximum location.

Finds global minimum and maximum in array or subarray

Pointer to returned minimum location. Pointer to returned maximum location. The optional mask that is used to select a subarray.

Finds global minimum and maximum in array or subarray

Pointer to returned minimum value. Pointer to returned maximum value. Pointer to returned minimum location. Pointer to returned maximum location.

Finds global minimum and maximum in array or subarray

Pointer to returned minimum value. Pointer to returned maximum value. Pointer to returned minimum location. Pointer to returned maximum location. The optional mask that is used to select a subarray.

Finds per-element minimum of array and scalar

The scalar value. The destination array.

Moments

(For images only) If the flag is non-zero, all the zero pixel values are treated as zeroes, all the others are treated as 1’s

Calculates per-element product of two arrays

The second source array. The destination array.

Calculates per-element product of two arrays

The second source array. The destination array. Optional scale factor

Calculates absolute array norm, absolute difference norm or relative difference norm

The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated.

Calculates absolute array norm, absolute difference norm or relative difference norm

The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. Type of norm

Calculates absolute array norm, absolute difference norm or relative difference norm

The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. Type of norm The optional operation mask.

Normalizes array to a certain norm or value range

The output array; in-place operation is supported.

Normalizes array to a certain norm or value range

The output array; in-place operation is supported. The minimum/maximum value of the output array or the norm of output array. The maximum/minimum value of the output array.

Normalizes array to a certain norm or value range

The output array; in-place operation is supported. The minimum/maximum value of the output array or the norm of output array. The maximum/minimum value of the output array. The normalization type.

Normalizes array to a certain norm or value range

The output array; in-place operation is supported. The minimum/maximum value of the output array or the norm of output array. The maximum/minimum value of the output array. The normalization type. The operation mask. Makes the function consider and normalize only certain array elements.

Performs per-element bit-wise inversion of array elements

The destination array.

Calculates per-element bit-wise disjunction of two arrays

The second source array. The destination array.

Calculates per-element bit-wise disjunction of two arrays

The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Calculates per-element bit-wise disjunction of array and scalar

Scalar to use in the operation. The destination array.

Calculates per-element bit-wise disjunction of array and scalar

Scalar to use in the operation. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Performs perspective matrix transform of vector array

The destination three-channel floating-point array. 3×3 or 4×4 transformation matrix.

Point in contour test

The point tested against the contour. If it is true, the function estimates distance from the point to the nearest contour edge. The function cvPointPolygonTest determines whether the point is inside contour, outside, or lies on an edge (or coinsides with a vertex). It returns positive, negative or zero value, correspondingly. When measure_dist=0, the return value is +1, -1 and 0, respectively. When measure_dist≠0, it is a signed distance between the point and the nearest contour edge.

Draws simple or thick polygons

Array of pointers to polylines. Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. Polyline color.

Draws simple or thick polygons

Array of pointers to polylines. Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. Polyline color. Thickness of the polyline edges.

Draws simple or thick polygons

Array of pointers to polylines. Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. Polyline color.

Draws simple or thick polygons

Raises every array element to power

The destination array, should be the same type as the source. The exponent of power.

Calculates feature map for corner detection

Image to store the corner candidates.

Calculates feature map for corner detection

Image to store the corner candidates. Aperture parameter for Sobel operator.

Return pointer to the particular array element

The first zero-based component of the element index pointer to the particular array element

Return pointer to the particular array element

The first zero-based component of the element index Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

The first zero-based component of the element index The second zero-based component of the element index pointer to the particular array element

Return pointer to the particular array element

The first zero-based component of the element index The second zero-based component of the element index Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index pointer to the particular array element

Return pointer to the particular array element

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

Array of the element indices pointer to the particular array element

Return pointer to the particular array element

Array of the element indices Type of matrix elements pointer to the particular array element

Return pointer to the particular array element

Array of the element indices Type of matrix elements Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. Optional input parameter for sparse matrices. If the pointer is not NULL, the function does not recalculate the node hash value, but takes it from the specified location. It is useful for speeding up pair-wise operations pointer to the particular array element

Draws text string

String to print. Coordinates of the bottom-left corner of the first letter. Pointer to the font structure. Text color.

Downsamples image.

The destination image, should have 2x smaller width and height than the source.

Downsamples image.

The destination image, should have 2x smaller width and height than the source. Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported.

Does meanshift image segmentation.

The destination image of the same format and the same size as the source. The spatial window radius. The color window radius.

Does meanshift image segmentation.

The destination image of the same format and the same size as the source. The spatial window radius. The color window radius. Maximum level of the pyramid for the segmentation.

Does meanshift image segmentation.

The destination image of the same format and the same size as the source. The spatial window radius. The color window radius. Maximum level of the pyramid for the segmentation. Termination criteria: when to stop meanshift iterations.

Upsamples image.

The destination image, should have 2x smaller width and height than the source.

Upsamples image.

The destination image, should have 2x smaller width and height than the source. Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported.

Randomly shuffles the array elements

The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used.

Randomly shuffles the array elements

The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used. The relative parameter that characterizes intensity of the shuffling performed.

Fills matrix with given range of numbers as following: arr(i,j) = (end-start) * (i*cols(arr)+j) / (cols(arr)*rows(arr))

The lower inclusive boundary of the range. The upper exclusive boundary of the range.

Draws simple, thick or filled rectangle

X-coordinate of the one of the rectangle vertices. Y-coordinate of the one of the rectangle vertices. X-coordinate of the opposite rectangle vertex. Y-coordinate of the opposite rectangle vertex. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

One of the rectangle vertices. Opposite rectangle vertex. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

One of the rectangle vertices. Opposite rectangle vertex. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Rectangle. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Rectangle. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Rectangle. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. Type of the line, see cvLine description.

Draws simple, thick or filled rectangle

One of the rectangle vertices. Opposite rectangle vertex. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Rectangle. Line color (RGB) or brightness (grayscale image).

Draws simple, thick or filled rectangle

Rectangle. Line color (RGB) or brightness (grayscale image). Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle.

Draws simple, thick or filled rectangle

Reduces matrix to a vector

The output single-row/single-column vector that accumulates somehow all the matrix rows/columns.

Reduces matrix to a vector

The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. The dimension index along which the matrix is reduce. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column. -1 means that the dimension is chosen automatically by analysing the dst size.

Reduces matrix to a vector

Releases array data.

Applies generic geometrical transformation to the image.

Destination image. The map of x-coordinates (32fC1 image). The map of y-coordinates (32fC1 image).

Applies generic geometrical transformation to the image.

Destination image. The map of x-coordinates (32fC1 image). The map of y-coordinates (32fC1 image). A combination of interpolation method and the optional flag(s).

Applies generic geometrical transformation to the image.

Destination image. The map of x-coordinates (32fC1 image). The map of y-coordinates (32fC1 image). A combination of interpolation method and the optional flag(s). A value used to fill outliers.

Fill destination array with tiled source array

Destination array, image or matrix.

Changes shape of matrix/image without copying data

Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged.

Changes shape of matrix/image without copying data

Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged. New number of rows. new_rows = 0 means that number of rows remains unchanged unless it needs to be changed according to new_cn value. destination array to be changed.

Changes shape of matrix/image without copying data

Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged.

Changes shape of matrix/image without copying data

Changes shape of multi-dimensional array w/o copying data

Size of output header to distinguish between IplImage, CvMat and CvMatND output headers. Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged. New number of dimensions. new_dims = 0 means that number of dimensions remains the same. Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used

Changes shape of multi-dimensional array w/o copying data

Output header to be filled. New number of channels. new_cn = 0 means that number of channels remains unchanged. New number of dimensions. new_dims = 0 means that number of dimensions remains the same. Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used

Resizes image src so that it fits exactly to dst. If ROI is set, the function consideres the ROI as supported as usual.

Destination image.

Resizes image src so that it fits exactly to dst. If ROI is set, the function consideres the ROI as supported as usual.

Destination image. Interpolation method.

Starting the line point. Ending the line point. Buffer to store the line points. The line connectivity, 4 or 8.

Calculates sum of scaled array and another array

Scale factor for the first array. The second source array. The destination array

Calculates sum of scaled array and another array

Scale factor for the first array. The second source array. The destination array

Sets every element of array to given value

Fill value.

Sets every element of array to given value

Fill value. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Change the particular array element

The first zero-based component of the element index The assigned value

Change the particular array element

The first zero-based component of the element index The second zero-based component of the element index The assigned value

Change the particular array element

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index The assigned value

Change the particular array element

The assigned value Array of the element indices

Assigns user data to the array header. Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function.

User data. Full row length in bytes.

Assigns user data to the array header. Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function.

User data. Full row length in bytes.

Initializes scaled identity matrix

The value to assign to the diagonal elements.

Change the particular array element

The first zero-based component of the element index The assigned value

Change the particular array element

The first zero-based component of the element index The second zero-based component of the element index The assigned value

Change the particular array element

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index The assigned value

Change the particular array element

The assigned value Array of the element indices

Clears the array

Smooths the image in one of several ways.

The destination image.

Smooths the image in one of several ways.

The destination image. Type of the smoothing.

Smooths the image in one of several ways.

The destination image. Type of the smoothing. The first parameter of smoothing operation.

Smooths the image in one of several ways.

The destination image. Type of the smoothing. The first parameter of smoothing operation. The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. In case of Gaussian kernel this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size.

Smooths the image in one of several ways.

Calculates first, second, third or mixed image derivatives using extended Sobel operator

Destination image. Order of the derivative x. Order of the derivative y.

Calculates first, second, third or mixed image derivatives using extended Sobel operator

Destination image. Order of the derivative x. Order of the derivative y. Size of the extended Sobel kernel.

Sorts the rows/cols of an array ascending/descending

Optional destination array

Sorts the rows/cols of an array ascending/descending

Optional destination array Index matrix

Sorts the rows/cols of an array ascending/descending

Optional destination array Index matrix Sorting parameter

Divides multi-channel array into several single-channel arrays or extracts a single channel from the array

Destination channel 0 Destination channel 1 Destination channel 2 Destination channel 3

Divides multi-channel array into several single-channel arrays or extracts a single channel from the array

Destination channel 0 Destination channel 1 Destination channel 2 Destination channel 3

Adds the square of source image to accumulator

Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point.

Adds the square of source image to accumulator

Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. Optional operation mask.

Initializes contour scanning process

Container of the retrieved contours. CvContourScanner

Initializes contour scanning process

Container of the retrieved contours. Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. CvContourScanner

Initializes contour scanning process

Container of the retrieved contours. Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. Retrieval mode; see cvFindContours. CvContourScanner

Initializes contour scanning process

Container of the retrieved contours. Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. Retrieval mode; see cvFindContours. Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. CvContourScanner

Initializes contour scanning process

Computes per-element difference between two arrays

The second source array. The destination array.

Computes per-element difference between two arrays

The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Computes difference between array and scalar

Subtracted scalar. The destination array.

Computes difference between array and scalar

Subtracted scalar. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Computes difference between scalar and array

Scalar to subtract from. The destination array.

Computes difference between scalar and array

Scalar to subtract from. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Summarizes array elements

sum S of array elements, independently for each channel

Performs singular value decomposition of real floating-point matrix

Resulting singular value matrix (M×N or N×N) or vector (N×1).

Performs singular value decomposition of real floating-point matrix

Resulting singular value matrix (M×N or N×N) or vector (N×1). Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped.

Performs singular value decomposition of real floating-point matrix

Applies fixed-level threshold to array elements.

Destination array; must be either the same type as src or 8-bit. Threshold value. Maximum value to use with CV_THRESH_BINARY and CV_THRESH_BINARY_INV thresholding types. Thresholding type.

Returns trace of matrix

sum of diagonal elements of the matrix src1

Transposes matrix

The destination matrix.

Transposes matrix

The destination matrix.

Transforms image to compensate lens distortion.

The output (corrected) image. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2].

Transforms image to compensate lens distortion.

The output (corrected) image. The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2].

Applies perspective transformation to the image.

Destination image. 3x3 transformation matrix.

Applies perspective transformation to the image.

Destination image. 3x3 transformation matrix. A combination of interpolation method and the optional flags.

Applies perspective transformation to the image.

Destination image. 3x3 transformation matrix. A combination of interpolation method and the optional flags. A value used to fill outliers.

Does watershed segmentation.

The input/output 32-bit single-channel image (map) of markers.

Performs per-element bit-wise "exclusive or" operation on two arrays

The second source array. The destination array. am>

Performs per-element bit-wise "exclusive or" operation on two arrays

The second source array. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Performs per-element bit-wise "exclusive or" operation on array and scalar

Scalar to use in the operation. The destination array.

Performs per-element bit-wise "exclusive or" operation on array and scalar

Scalar to use in the operation. The destination array. Operation mask, 8-bit single channel array; specifies elements of destination array to be changed.

Default constructor

Constructor

If true, this matrix will be disposed by GC automatically.

Clean up any resources being used.

Get number of dimensions

Get type of the array

Get number of channels

Get bit Depth

Return the particular array element (cvGet1D/Set1D)

The first zero-based component of the element index

Return the particular array element (cvGet2D/Set2D)

The first zero-based component of the element index The second zero-based component of the element index

Return the particular array element (cvGet3D/Set3D)

The first zero-based component of the element index The second zero-based component of the element index The third zero-based component of the element index

Finds lines in binary image using Hough transform.

Distance resolution in pixel-related units. Angle resolution measured in radians. Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold.

Finds lines in binary image using Hough transform.

Composes multi-channel array from several single-channel arrays or inserts a single channel into the array. (cvMerge)

Input channel 0 Input channel 1 Input channel 2 Input channel 3

Composes multi-channel array from several single-channel arrays or inserts a single channel into the array. (cvCvtPlaneToPix)

Input channel 0 Input channel 1 Input channel 2 Input channel 3

Fills array with random numbers and updates the RNG state

RNG state initialized by cvRNG. Distribution type. The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers.

Name of the file.

Extract this image to the memory using cvEncodeImage

Image extension to decide encoding format. Encoding options.

Extract this image to the memory using cvEncodeImage

Destination stream. Image extension to decide encoding format. Encoding options.

Position in relative units

Start of the file

End of the file

Error status

everithing is ok [CV_StsOk]

pseudo error for back trace [CV_StsBackTrace]

unknown /unspecified error [CV_StsError]

internal error (bad state) [CV_StsInternal]

insufficient memory [CV_StsNoMem]

function arg/param is bad [CV_StsBadArg]

unsupported function [CV_StsBadFunc]

iter. didn't converge [CV_StsNoConv]

tracing [CV_StsAutoTrace]

image header is NULL [CV_HeaderIsNull]

image size is invalid [CV_BadImageSize]

offset is invalid [CV_BadOffset]

[CV_BadOffset]

[CV_BadStep]

[CV_BadModelOrChSeq]

[CV_BadNumChannels]

[CV_BadNumChannel1U]

[CV_BadDepth]

[CV_BadAlphaChannel]

[CV_BadOrder]

[CV_BadOrigin]

[CV_BadAlign]

[CV_BadCallBack]

[CV_BadTileSize]

[CV_BadCOI]

[CV_BadROISize]

[CV_MaskIsTiled]

null pointer [CV_StsNullPtr]

incorrect vector length [CV_StsVecLengthErr]

incorr. filter structure content [CV_StsFilterStructContentErr]

incorr. transform kernel content [CV_StsKernelStructContentErr]

incorrect filter ofset value [CV_StsFilterOffsetErr]

the input/output structure size is incorrect [CV_StsBadSize]

division by zero [CV_StsDivByZero]

in-place operation is not supported [CV_StsInplaceNotSupported]

request can't be completed [CV_StsObjectNotFound]

formats of input/output arrays differ [CV_StsUnmatchedFormats]

flag is wrong or not supported [CV_StsBadFlag]

bad CvPoint [CV_StsBadPoint]

bad format of mask (neither 8uC1 nor 8sC1) [CV_StsBadMask]

sizes of input/output structures do not match [CV_StsUnmatchedSizes]

the data format/type is not supported by the function [CV_StsUnsupportedFormat]

some of parameters are out of range [CV_StsOutOfRange]

invalid syntax/structure of the parsed file [CV_StsParseError]

the requested function/feature is not implemented [CV_StsNotImplemented]

an allocated block has been corrupted [CV_StsBadMemBlock]

Error mode

The program is terminated after error handler is called. This is the default value. It is useful for debugging, as the error is signalled immediately after it occurs. However, for production systems other two methods may be preferable as they provide more control. [CV_ErrModeLeaf]

The program is not terminated, but the error handler is called. The stack is unwinded (it is done w/o using C++ exception mechanism). User may check error code after calling Cxcore function with cvGetErrStatus and react. [CV_ErrModeParent]

Similar to Parent mode, but no error handler is called. [CV_ErrModeSilent]

4-character code of codec used to compress the frames.

pt[i]

next[i]

Handles loading embedded dlls into memory, based on http://stackoverflow.com/questions/666799/embedding-unmanaged-dll-into-a-managed-c-sharp-dll.

This code is based on https://github.com/charlesw/tesseract

The default base directory name to copy the assemblies too.

Map processor

Used as a sanity check for the returned processor architecture to double check the returned value.

Additional user-defined DLL paths

constructor

Get's the current process architecture while keeping track of any assumptions or possible errors.

Determines if the dynamic link library file name requires a suffix and adds it if necessary.

Given the processor architecture, returns the name of the platform.

List of attributes

const char** attr;

struct CvAttrList* next;

NULL-terminated array of (attribute_name,attribute_value) pairs

pointer to next chunk of the attributes list

sizeof(CvAttrList)

initializes CvAttrList structure

array of (attribute_name,attribute_value) pairs

initializes CvAttrList structure

array of (attribute_name,attribute_value) pairs pointer to next chunk of the attributes list

Rotated 2D box

Center of the box.

Box width and length.

Angle between the horizontal axis and the first side (i.e. length) in degrees

sizeof(CvBox2D)

Constructor

Finds box vertices

Array of vertices

Specifies whether this object contains the same members as the specified Object.

The Object to test. This method returns true if obj is the same type as this object and has the same members as this object.

Returns a hash code for this object.

An integer value that specifies a hash value for this object.

Converts this object to a human readable string.

A string that represents this object.

Chain Reader

Target chain

Default constructor

Initialize by cvStartReadChainPoints

Pointer to chain

Clean up any resources being used.

sizeof(CvChainPtReader)

Data pointer (CvChainPtReader*)

schar deltas[8][2]

Initializes chain reader

Pointer to chain

Gets next chain point

Current chain point.

CvConDensation

Track whether Dispose has been called

Initialize from pointer

struct CvConDensation*

Allocates ConDensation filter structure

Dimension of the state vector. Dimension of the measurement vector. Number of samples.

Clean up any resources being used.

sizeof(CvConDensation)

Dimension of measurement vector

Dimension of state vector

Matrix of the linear Dynamics system

Vector of State

Number of the Samples

Array of the Sample Vectors

Temporary array of the Sample Vectors

Confidence for each Sample

Cumulative confidence

Temporary vector

RandomVector to update sample set

A balanced kd-tree index of feature vectors

Track whether Dispose has been called

Constructs a tree of feature vectors

n x d matrix of n d-dimensional feature vectors (CV_32FC1 or CV_64FC1).

Constructs from native pointer

struct CvFeatureTree*

Constructs a tree of feature vectors

n x d matrix of n d-dimensional feature vectors (CV_32FC1 or CV_64FC1).

Constructs kd-tree from set of feature descriptors

Constructs spill-tree from set of feature descriptors

Clean up any resources being used.

Finds approximate k nearest neighbors of given vectors using best-bin-first search.

m x d matrix of (row-)vectors to find the nearest neighbors of. m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. m x k matrix of distances to k nearest neighbors.

Finds approximate k nearest neighbors of given vectors using best-bin-first search.

Performs orthogonal range seaching on the given kd-tree.

1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving minimum value for each dimension. 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving maximum value for each dimension. 1 x m or m x 1 vector (CV_32SC1) to contain output row indices (referring to matrix passed to cvCreateFeatureTree). the number of such vectors found.

Edge of graph

Initializes from native pointer

sizeof(CvGraphEdge)

Edge flags

Edge weight

The next edges in the incidence lists for staring (0) and ending (1) vertices

The starting (0) and ending (1) vertices

CvGraphScanner

Track whether Dispose has been called

Initialize from pointer

Creates structure for depth-first graph traversal

Graph.

Creates structure for depth-first graph traversal

Graph. Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices).

Creates structure for depth-first graph traversal

Clean up any resources being used.

sizeof(CvGraphScanner)

Current graph vertex (or current edge origin)

Current graph edge destination vertex

Current edge

the graph

the graph vertex stack

the lower bound of certainly visited vertices

event mask

Returns index of graph vertex

The function cvNextGraphItem traverses through the graph until an event interesting to the user (that is, an event, specified in the mask in cvCreateGraphScanner call) is met or the traversal is over. In the first case it returns one of the events, listed in the description of mask parameter above and with the next call it resumes the traversal. In the latter case it returns CV_GRAPH_OVER (-1). When the event is CV_GRAPH_VERTEX, or CV_GRAPH_BACKTRACKING or CV_GRAPH_NEW_TREE, the currently observed vertex is stored in scanner->vtx. And if the event is edge-related, the edge itself is stored at scanner->edge, the previously visited vertex - at scanner->vtx and the other ending vertex of the edge - at scanner->dst.

Vertex of graph

Allocates memory

Initializes from native pointer

sizeof(CvGraphVtx)

Edge flags

The first incident edge

a single tree classifier (stump in the simplest case) that returns the response for the feature at the particular image location (i.e. pixel sum over subrectangles of the window) and gives out a value depending on the responce

Initializes from native pointer

struct CvHaarClassifier*

sizeof(CvHaarClassifier)

Number of nodes in the decision tree

Array of haar features

branch threshold. if feature responce is <= threshold, left branch is chosen, otherwise right branch is chosed.

index of the left child (or negated index if the left child is a leaf)

index of the right child (or negated index if the right child is a leaf)

output value correponding to the leaf.

A haar feature which consists of 2-3 rectangles with appropriate weights.

Initializes from native pointer

struct CvHaarFeature*

sizeof(CvHaarClassifier)

0 means up-right feature, 1 means 45--rotated feature

Elements of the haar feature

An element of a haar feature

a boosted battery of classifiers(=stage classifier): the stage classifier returns 1 if the sum of the classifiers' responces is greater than threshold and 0 otherwise

Initializes from native pointer

struct CvHaarStageClassifier*

sizeof(CvHaarStageClassifier)

Number of classifiers in the battery

Threshold for the boosted classifier

Array of classifiers

Hu moments

Default constructor

Initialize by cvGetHuMoments

Pointer to the moment state structure.

CvLineIterator

Constructor

Initializes line iterator

Image to sample the line from. First ending point of the line segment. Second ending point of the line segment. The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm.

Initializes line iterator

Image to sample the line from. First ending point of the line segment. Second ending point of the line segment. The scanned line connectivity, 4 or 8. The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm.

Initializes line iterator

Image to sample the line from. First ending point of the line segment. Second ending point of the line segment. The scanned line connectivity, 4 or 8. The flag, indicating whether the line should be always scanned from the left-most point to the right-most out of pt1 and pt2 (leftToRight=true), or it is scanned in the specified order, from pt1 to pt2 (leftToRight=false). The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm.

Initializes line iterator

Clean up any resources being used.

sizeof(CvLineIterator)

CV_NEXT_LINE_POINT

Gets the value of the current point

Supports a simple iteration over a generic collection.

Memory storage block

Constructs from native pointer

struct CvMemBlock*

sizeof(CvMemBlock)

Memory storage position

Default constructor

Initializes from native pointer

struct CvMemStoragePos*

sizeof(CvMemStoragePos)

Moment state structure

Default constructor

Initialize by cvMoments

Image (1-channel or 3-channel with COI set) or polygon (CvSeq of points or a vector of points). (For images only) If the flag is non-zero, all the zero pixel values are treated as zeroes, all the others are treated as 1’s.

Retrieves central moment from moment state structure

x order of the retrieved moment, x_order >= 0 y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 Central moment

Calculates seven Hu invariants

Pointer to Hu moments structure

Retrieves normalized central moment from moment state structure

x order of the retrieved moment, x_order >= 0 y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 Central moment

Retrieves spatial moment from moment state structure

x order of the retrieved moment, x_order >= 0 y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 Spatial moments

Structure containing object information

Track whether Dispose has been called

Constructor (cvCreatePOSITObject)

Points of the 3D object model.

Constructs from pointer

struct CvPOSITObject*

Clean up any resources being used.

Implements POSIT algorithm

Object points projections on the 2D image plane. Focal length of the camera used. Termination criteria of the iterative POSIT algorithm. Matrix of rotations. Translation vector.

CvRandState

typedef struct CvRandState { CvRNG _state; /* RNG state (the current seed and carry)*/ int _disttype; /* distribution type */ CvScalar _param[2]; /* parameters of RNG */ } CvRandState;

RNG _state (the current seed and carry)

distribution type

parameters of RNG

Initializes from pointer

Fills array with random numbers

The array to randomize

Initialize CvRandState structure

The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. Seed value

Initialize CvRandState structure

Changes RNG range while preserving RNG _state

sparse array iterator

Target sparse mat

Default constructor

Initializes with CvSparseMat

Input array

Clean up any resources being used.

sizeof(CvSparseMatIterator)

Moves iterator to the next sparse matrix element and returns pointer to it.

Initializes sparse array elements iterator

Input array the first sparse matrix element

An element of CvSparseMat

Default constructor

CvSparseNode*

sizeof(CvSparseNode)

Class that is used to traverse trees

Default Constructor

Construct by cvInitTreeNodeIterator

Returns the currently observed node and moves iterator toward the next node

Returns the currently observed node and moves iterator toward the previous node

Class that is used to traverse trees

Default Constructor

Construct by cvInitTreeNodeIterator

Convert to generic class

Returns the currently observed node and moves iterator toward the next node

Returns the currently observed node and moves iterator toward the previous node

Sequence writer

Track whether Dispose has been called

Default constructor

Initializes process of writing data to sequence (cvStartAppendToSeq).

Pointer to the sequence. Writer state; initialized by the function.

Creates new sequence and initializes writer for it (cvStartWriteSeq).

Initializes from pointer

CvSeqWriter*

Clean up any resources being used.

sizeof(CvSeqWriter)

size of sequence header

Sequence, beign read

current block

pointer to element be read next

pointer to the beginning of block

pointer to the End of block

Finishes process of writing sequence

the pointer to the written sequence.

Updates sequence headers from the writer state (cvFlushSeqWriter).

(CV_WRITE_SEQ_ELEM_VAR)

(CV_WRITE_SEQ_ELEM)

Sequence writer

Default constructor

Initializes process of writing data to sequence (cvStartAppendToSeq).

Pointer to the sequence. Writer state; initialized by the function.

Creates new sequence and initializes writer for it (cvStartWriteSeq).

Initializes from non generic writer

Initializes from pointer

CvSeqWriter*

Clean up any resources being used.

(CV_WRITE_SEQ_ELEM)

Contour tree

Initializes from native pointer

Creates hierarchical representation of contour

Input contour. Container for output tree. Approximation accuracy.

sizeof(CvContourTree)

The first point of the binary tree root segment

The last point of the binary tree root segment

Restores contour from tree.

Container for the reconstructed contour. Criteria, where to stop reconstruction.

Oriented or unoriented weigted graph

Default constructor

Creates empty graph

Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. Graph header size; may not be less than sizeof(CvGraph). Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) The graph container. The function cvCreateGraph creates an empty graph and returns it.

Initializes from native pointer

struct CvGraph*

sizeof(CvGraph)

Set of edges

Returns index of graph vertex

The function cvClearGraph removes all vertices and edges from the graph. The function has O(1) time complexity.

Clone graph

Container for the copy. The function cvCloneGraph creates full copy of the graph. If the graph vertices or edges have pointers to some external data, it still be shared between the copies. The vertex and edge indices in the new graph may be different from the original, because the function defragments the vertex and edge sets.

Finds edge in graph

Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists.

Finds edge in graph

Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists.

Finds edge in graph

Adds edge to graph

Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. Optional output parameter to contain the address of the inserted edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds edge to graph

Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. Optional input parameter, initialization data for the edge. Optional output parameter to contain the address of the inserted edge. The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default.

Adds vertex to graph

The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index.

Adds vertex to graph

Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index.

Adds vertex to graph

Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). The address of the new vertex is written there. The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index.

Returns index of graph edge

Graph edge. The function cvGraphEdgeIdx returns index of the graph edge.

Returns count of edges

Returns count of vertex

Removes edge from graph

Index of the starting vertex of the edge. Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphRemoveEdge removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing.

Removes edge from graph

Starting vertex of the edge. Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. The function cvGraphRemoveEdgeByPtr removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing.

Removes vertex from graph

Index of the removed vertex. The function cvGraphRemoveAddVtx removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the input vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph.

Removes vertex from graph

Vertex to remove The function cvGraphRemoveVtxByPtr removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph.

Counts edges indicent to the vertex

Index of the graph vertex. The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming.

Counts edges indicent to the vertex

Index of the graph vertex. The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming.

Returns index of graph vertex

Graph vertex. The function cvGraphVtxIdx returns index of the graph vertex.

The user-defined distance function for cvCalcEMD2. It takes coordinates of two points and returns the distance between the points.

WndProc

Windows message ID

Angle Unit for cvCartToPolar

Angle in radians

Angle in degrees

Similarity measure (cvMatchContourTrees)

[CV_CONTOUR_TREES_MATCH_I1]

Orientation for Convex Hull function

Clockwise [CV_CLOCKWISE]

Counter clockwise [CV_COUNTER_CLOCKWISE]

Event mask indicating which events are interesting to the user

Stop at the graph vertices visited for the first time [CV_GRAPH_VERTEX]

Stop at tree edges (tree edge is the edge connecting the last visited vertex and the vertex to be visited next) [CV_GRAPH_TREE_EDGE]

Stop at back edges (back edge is an edge connecting the last visited vertex with some of its ancestors in the search tree) [CV_GRAPH_BACK_EDGE]

Stop at forward edges (forward edge is an edge conecting the last visited vertex with some of its descendants in the search tree). The forward edges are only possible during oriented graph traversal) [CV_GRAPH_FORWARD_EDGE]

Stop at cross edges (cross edge is an edge connecting different search trees or branches of the same tree. The cross edges are only possible during oriented graphs traversal) [CV_GRAPH_CROSS_EDGE]

Stop and any edge (tree, back, forward and cross edges) [CV_GRAPH_ANY_EDGE]

Stop in the beginning of every new search tree. When the traversal procedure visits all vertices and edges reachible from the initial vertex (the visited vertices together with tree edges make up a tree), it searches for some unvisited vertex in the graph and resumes the traversal process from that vertex. Before starting a new tree (including the very first tree when cvNextGraphItem is called for the first time) it generates CV_GRAPH_NEW_TREE event. For unoriented graphs each search tree corresponds to a connected component of the graph. [CV_GRAPH_NEW_TREE]

Stop at every already visited vertex during backtracking - returning to already visited vertexes of the traversal tree. [CV_GRAPH_BACKTRACKING]

All events are interesting [CV_GRAPH_OVER]

All events are interesting [CV_GRAPH_ALL_ITEMS]

Flags for PCA operations

The vectors are stored as rows (i.e. all the components of a certain vector are stored continously) [CV_PCA_DATA_AS_ROW]

The vectors are stored as columns (i.e. values of a certain vector component are stored continuously) [CV_PCA_DATA_AS_COL]

Use pre-computed average vector [CV_PCA_USE_AVG]

cvConvertImage operation flags

flip the image vertically [CV_CVTIMG_FLIP]

swap red and blue channels [CV_CVTIMG_SWAP_RB]

PixelConnectivity for LineIterator

Connectivity 4 (N,S,E,W)

Connectivity 8 (N,S,E,W,NE,SE,SW,NW)

The operation flags for cvStereoRectify

Default value (=0). the function can shift one of the image in horizontal or vertical direction (depending on the orientation of epipolar lines) in order to maximise the useful image area.

the function makes the principal points of each camera have the same pixel coordinates in the rectified views. [CV_CALIB_ZERO_DISPARITY]

Origin of IplImage

top-left origin [IPL_ORIGIN_TL (0)]

bottom-left origin (Windows bitmaps style) [IPL_ORIGIN_BL (1)]

circle structure retrieved from cvHoughCircle

Center coordinate of the circle

Radius

Constructor

center radius