Computes Robot-World and Hand-Eye calibration matrices.

Computes Hand-Eye calibration matrices.

Check chessboard corners.

Converts points from Euclidean to homogeneous space.

Computes epilines in one view for a set of points in the other view.

Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).

Renders the detected chessboard corners.

Computes an optimal affine transformation between two 2D point sets.

Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

Finds the positions of the internal corners of the chessboard.

Calculates an essential matrix from the corresponding points in two images.

Finds the camera intrinsic and extrinsic parameters from pairs of corresponding image and object points arrays.

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

Projects 3D points to an image plane.

Converts a Rotation Matrix to a Rvec vector.

Finds an object pose from 3D-2D point correspondences. This function returns the rotation and the translation vectors that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame.

Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.

Computes stereo correspondence using the block matching algorithm.

Computes rectification transforms for each head of a calibrated stereo camera.

This function reconstructs 3-dimensional points (in homogeneous coordinates) by using their observations with a stereo camera.

Creates simple array with object points.

Given an original color image, two differently colored versions of this image can be mixed seamlessly.

Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional). As the image denoising, in particular, may be seen as the variational problem, primal-dual algorithm then can be used to perform denoising and this is exactly what is implemented.

Filtering is the fundamental operation in image and video processing. Edge-preserving smoothing filters are used in many different applications.

Perform image denoising using Non-local Means Denoising algorithm.

Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image.

By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect. Here Canny Edge Detector is used.

Enables or disables the optimized code.

Draws a circle.

Draws a simple or thick elliptic arc or fills an ellipse sector.

Fills the area bounded by one or more polygons.

Calculates the width and height of a text string.

Draws several polygonal curves.

Draws a simple, thick, or filled up-right rectangle.

BRISK keypoint detector and descriptor extractor.

Feature detection using the good features to track function.

ORB keypoint detector and descriptor extractor.

Extracting blobs from an image.

Finds edges in an image using Canny algorithm.

Harris corner detector.

Refines the corner locations.

Finds circles in a grayscale image using a Hough transform.

Finds lines segments in a binary image using probabilistic Hough transform.

Calculates the affine transform from 3 corresponding points.

Prepares matrix to be used with cvWarpAffine.

Calculates the perspective transform from four pairs of corresponding points.

Prepares matrix to be used with cvWarpPerspective.

Calculates the affine matrix of 2D rotation.

Prepares matrix to be used with cvWarpAffine.

Inverts an affine transformation.

Prepares matrix to be used with cvWarpAffine.

Resizes an image.

Undistorts points.

Applies a perspective transformation to an image.

Applies bilateral filter to the image.

Computes source location of extrapolated pixel.

Constructs Gaussian pyramid for an image.

Dilates an image by using a specific structuring element.

Convolves an image with the kernel.

Returns filter coefficients for computing spatial image derivatives.

Prepares matrices to be used with cvSepFilter2D or cvFilter2D.

Returns Gaussian filter coefficients.

Prepares matrix to be used with cvSepFilter2D or cvFilter2D.

Calculates the Laplacian of an image.

Returns magic border value for erosion and dilation.

Smoothes an image and downsamples it.

Calculates the first x- or y- image derivative using Scharr operator.

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

Applies an adaptive threshold to an image.

Blend images.

Calculates the distance to the closest zero pixel for each pixel of the source image.

Runs the GrabCut algorithm.

Calculates the integral of an image.

Applies a fixed-level threshold to each image element.

Adds image to the accumulator.

Adds the square of the source image to the accumulator.

K-nearest neighbours based background segmentation algorithm.

Finds an moving object center, size, and orientation.

DIS optical flow algorithm.

Standard Kalman filter.

Calculate an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.

Calculates array histogram. This function perform cvCalcHist inside.

Equalizes histogram of image using adaptive histogram equalization.

Equalizes the histogram of a grayscale image.

Approximates polygonal curve(s) with the specified precision.

Calculates the up-right bounding rectangle of a point set.

Computes the connected components labeled image of boolean image and also produces a statistics output for each label

Finds the convex hull of a point set.

Finds the contours in a binary image.

Fits an ellipse around a set of 2D points.

Fits a line to a 2D or 3D point set.

Finds arbitrary template in the grayscale image using Generalized Hough Transform.

Finds arbitrary template in the grayscale image using Generalized Hough Transform.

Finds intersection of two convex polygons.

Compares two shapes.

Finds a rotated rectangle of the minimum area enclosing the input 2D point set.

Finds a rotated triangle of the minimum area enclosing the input 2D point set.

Performs point-in-contour test.

Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.