/home/grier/opencv/opencv/modules/imgproc/include/opencv2/imgproc/imgproc.hpp File Reference

The Image Processing. More...

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Classes

class  cv::BaseColumnFilter
class  cv::BaseFilter
class  cv::BaseRowFilter
struct  CvLSHOperations
class  cv::FilterEngine
struct  lsh_hash
class  cv::Moments
 raster image moments More...

Namespaces

namespace  cv

Enumerations

enum  {
  cv::BORDER_REPLICATE = IPL_BORDER_REPLICATE, cv::BORDER_CONSTANT = IPL_BORDER_CONSTANT, cv::BORDER_REFLECT = IPL_BORDER_REFLECT, cv::BORDER_WRAP = IPL_BORDER_WRAP,
  cv::BORDER_REFLECT_101 = IPL_BORDER_REFLECT_101, cv::BORDER_REFLECT101 = BORDER_REFLECT_101, cv::BORDER_TRANSPARENT = IPL_BORDER_TRANSPARENT, cv::BORDER_DEFAULT = BORDER_REFLECT_101,
  cv::BORDER_ISOLATED = 16
}
 

various border interpolation methods

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enum  {
  cv::KERNEL_GENERAL = 0, cv::KERNEL_SYMMETRICAL = 1, cv::KERNEL_ASYMMETRICAL = 2, cv::KERNEL_SMOOTH = 4,
  cv::KERNEL_INTEGER = 8
}
 

type of the kernel

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enum  {
  cv::MORPH_ERODE = CV_MOP_ERODE, cv::MORPH_DILATE = CV_MOP_DILATE, cv::MORPH_OPEN = CV_MOP_OPEN, cv::MORPH_CLOSE = CV_MOP_CLOSE,
  cv::MORPH_GRADIENT = CV_MOP_GRADIENT, cv::MORPH_TOPHAT = CV_MOP_TOPHAT, cv::MORPH_BLACKHAT = CV_MOP_BLACKHAT
}
 

type of morphological operation

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enum  { cv::MORPH_RECT = 0, cv::MORPH_CROSS = 1, cv::MORPH_ELLIPSE = 2 }
 

shape of the structuring element

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enum  {
  cv::INTER_NEAREST = CV_INTER_NN, cv::INTER_LINEAR = CV_INTER_LINEAR, cv::INTER_CUBIC = CV_INTER_CUBIC, cv::INTER_AREA = CV_INTER_AREA,
  cv::INTER_LANCZOS4 = CV_INTER_LANCZOS4, cv::INTER_MAX = 7, cv::WARP_INVERSE_MAP = CV_WARP_INVERSE_MAP
}
 

interpolation algorithm

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enum  { cv::INTER_BITS = 5, cv::INTER_BITS2 = INTER_BITS*2, cv::INTER_TAB_SIZE = (1<<INTER_BITS), cv::INTER_TAB_SIZE2 = INTER_TAB_SIZE*INTER_TAB_SIZE }
enum  {
  cv::THRESH_BINARY = CV_THRESH_BINARY, cv::THRESH_BINARY_INV = CV_THRESH_BINARY_INV, cv::THRESH_TRUNC = CV_THRESH_TRUNC, cv::THRESH_TOZERO = CV_THRESH_TOZERO,
  cv::THRESH_TOZERO_INV = CV_THRESH_TOZERO_INV, cv::THRESH_MASK = CV_THRESH_MASK, cv::THRESH_OTSU = CV_THRESH_OTSU
}
 

type of the threshold operation

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enum  { cv::ADAPTIVE_THRESH_MEAN_C = 0, cv::ADAPTIVE_THRESH_GAUSSIAN_C = 1 }
 

adaptive threshold algorithm

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enum  { cv::PROJ_SPHERICAL_ORTHO = 0, cv::PROJ_SPHERICAL_EQRECT = 1 }
enum  { cv::GC_BGD = 0, cv::GC_FGD = 1, cv::GC_PR_BGD = 2, cv::GC_PR_FGD = 3 }
 

class of the pixel in GrabCut algorithm

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enum  { cv::GC_INIT_WITH_RECT = 0, cv::GC_INIT_WITH_MASK = 1, cv::GC_EVAL = 2 }
 

GrabCut algorithm flags.

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enum  { cv::INPAINT_NS = CV_INPAINT_NS, cv::INPAINT_TELEA = CV_INPAINT_TELEA }
 

the inpainting algorithm

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enum  { cv::FLOODFILL_FIXED_RANGE = 1 << 16, cv::FLOODFILL_MASK_ONLY = 1 << 17 }
enum  {
  cv::TM_SQDIFF = 0, cv::TM_SQDIFF_NORMED = 1, cv::TM_CCORR = 2, cv::TM_CCORR_NORMED = 3,
  cv::TM_CCOEFF = 4, cv::TM_CCOEFF_NORMED = 5
}
 

type of the template matching operation

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enum  { cv::RETR_EXTERNAL = CV_RETR_EXTERNAL, cv::RETR_LIST = CV_RETR_LIST, cv::RETR_CCOMP = CV_RETR_CCOMP, cv::RETR_TREE = CV_RETR_TREE }
 

mode of the contour retrieval algorithm

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enum  { cv::CHAIN_APPROX_NONE = CV_CHAIN_APPROX_NONE, cv::CHAIN_APPROX_SIMPLE = CV_CHAIN_APPROX_SIMPLE, cv::CHAIN_APPROX_TC89_L1 = CV_CHAIN_APPROX_TC89_L1, cv::CHAIN_APPROX_TC89_KCOS = CV_CHAIN_APPROX_TC89_KCOS }
 

the contour approximation algorithm

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Functions

CV_EXPORTS_W void cv::accumulate (const Mat &src, CV_IN_OUT Mat &dst, const Mat &mask=Mat())
 adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types.
CV_EXPORTS_W void cv::accumulateProduct (const Mat &src1, const Mat &src2, CV_IN_OUT Mat &dst, const Mat &mask=Mat())
 adds product of the 2 images to the accumulator (dst += src1*src2).
CV_EXPORTS_W void cv::accumulateSquare (const Mat &src, CV_IN_OUT Mat &dst, const Mat &mask=Mat())
 adds squared src image to the accumulator (dst += src*src).
CV_EXPORTS_W void cv::accumulateWeighted (const Mat &src, CV_IN_OUT Mat &dst, double alpha, const Mat &mask=Mat())
 updates the running average (dst = dst*(1-alpha) + src*alpha)
CV_EXPORTS_W void cv::adaptiveThreshold (const Mat &src, CV_OUT Mat &dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C)
 applies variable (adaptive) threshold to the image
void cv::approxPolyDP (const Mat &curve, CV_OUT vector< Point > &approxCurve, double epsilon, bool closed)
 approximates contour or a curve using Douglas-Peucker algorithm
CV_EXPORTS_W double cv::arcLength (const Mat &curve, bool closed)
 computes the contour perimeter (closed=true) or a curve length
CV_EXPORTS_W void cv::bilateralFilter (const Mat &src, CV_OUT Mat &dst, int d, double sigmaColor, double sigmaSpace, int borderType=BORDER_DEFAULT)
 smooths the image using bilateral filter
CV_EXPORTS_W void cv::blur (const Mat &src, CV_OUT Mat &dst, Size ksize, Point anchor=Point(-1,-1), int borderType=BORDER_DEFAULT)
 a synonym for normalized box filter
CV_EXPORTS_W int cv::borderInterpolate (int p, int len, int borderType)
 1D interpolation function: returns coordinate of the "donor" pixel for the specified location p.
CV_EXPORTS_W Rect cv::boundingRect (const Mat &points)
 computes the bounding rectangle for a contour
CV_EXPORTS_W void cv::boxFilter (const Mat &src, CV_OUT Mat &dst, int ddepth, Size ksize, Point anchor=Point(-1,-1), bool normalize=true, int borderType=BORDER_DEFAULT)
 smooths the image using the box filter. Each pixel is processed in O(1) time
void cv::buildPyramid (const Mat &src, CV_OUT vector< Mat > &dst, int maxlevel)
 builds the gaussian pyramid using pyrDown() as a basic operation
void cv::calcBackProject (const Mat *images, int nimages, const int *channels, const SparseMat &hist, Mat &backProject, const float **ranges, double scale=1, bool uniform=true)
 computes back projection for the set of images
void cv::calcBackProject (const Mat *images, int nimages, const int *channels, const Mat &hist, Mat &backProject, const float **ranges, double scale=1, bool uniform=true)
 computes back projection for the set of images
void cv::calcHist (const Mat *images, int nimages, const int *channels, const Mat &mask, SparseMat &hist, int dims, const int *histSize, const float **ranges, bool uniform=true, bool accumulate=false)
 computes the joint sparse histogram for a set of images.
void cv::calcHist (const Mat *images, int nimages, const int *channels, const Mat &mask, Mat &hist, int dims, const int *histSize, const float **ranges, bool uniform=true, bool accumulate=false)
 computes the joint dense histogram for a set of images.
double cv::compareHist (const SparseMat &H1, const SparseMat &H2, int method)
 compares two histograms stored in sparse arrays
CV_EXPORTS_W double cv::compareHist (const Mat &H1, const Mat &H2, int method)
 compares two histograms stored in dense arrays
CV_EXPORTS_W double cv::contourArea (const Mat &contour, bool oriented=false)
 computes the contour area
CV_EXPORTS_W void cv::convertMaps (const Mat &map1, const Mat &map2, CV_OUT Mat &dstmap1, CV_OUT Mat &dstmap2, int dstmap1type, bool nninterpolation=false)
 converts maps for remap from floating-point to fixed-point format or backwards
void cv::convexHull (const Mat &points, CV_OUT vector< Point > &hull, bool clockwise=false)
 computes convex hull for a set of 2D points.
void cv::convexHull (const Mat &points, CV_OUT vector< int > &hull, bool clockwise=false)
 computes convex hull for a set of 2D points.
CV_EXPORTS_W void cv::copyMakeBorder (const Mat &src, CV_OUT Mat &dst, int top, int bottom, int left, int right, int borderType, const Scalar &value=Scalar())
 copies 2D array to a larger destination array with extrapolation of the outer part of src using the specified border mode
CV_EXPORTS_W void cv::cornerEigenValsAndVecs (const Mat &src, CV_OUT Mat &dst, int blockSize, int ksize, int borderType=BORDER_DEFAULT)
 computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix.
CV_EXPORTS_W void cv::cornerHarris (const Mat &src, CV_OUT Mat &dst, int blockSize, int ksize, double k, int borderType=BORDER_DEFAULT)
 computes Harris cornerness criteria at each image pixel
CV_EXPORTS_W void cv::cornerMinEigenVal (const Mat &src, CV_OUT Mat &dst, int blockSize, int ksize=3, int borderType=BORDER_DEFAULT)
 computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
void cv::cornerSubPix (const Mat &image, vector< Point2f > &corners, Size winSize, Size zeroZone, TermCriteria criteria)
 adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria
Ptr< FilterEngine > cv::createBoxFilter (int srcType, int dstType, Size ksize, Point anchor=Point(-1,-1), bool normalize=true, int borderType=BORDER_DEFAULT)
 returns box filter engine
Ptr< FilterEngine > cv::createDerivFilter (int srcType, int dstType, int dx, int dy, int ksize, int borderType=BORDER_DEFAULT)
 returns filter engine for the generalized Sobel operator
Ptr< FilterEngine > cv::createGaussianFilter (int type, Size ksize, double sigma1, double sigma2=0, int borderType=BORDER_DEFAULT)
 returns the Gaussian filter engine
Ptr< FilterEngine > cv::createLinearFilter (int srcType, int dstType, const Mat &kernel, Point _anchor=Point(-1,-1), double delta=0, int _rowBorderType=BORDER_DEFAULT, int _columnBorderType=-1, const Scalar &_borderValue=Scalar())
 returns the non-separable linear filter engine
Ptr< FilterEngine > cv::createMorphologyFilter (int op, int type, const Mat &kernel, Point anchor=Point(-1,-1), int _rowBorderType=BORDER_CONSTANT, int _columnBorderType=-1, const Scalar &_borderValue=morphologyDefaultBorderValue())
 returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported.
Ptr< FilterEngine > cv::createSeparableLinearFilter (int srcType, int dstType, const Mat &rowKernel, const Mat &columnKernel, Point _anchor=Point(-1,-1), double delta=0, int _rowBorderType=BORDER_DEFAULT, int _columnBorderType=-1, const Scalar &_borderValue=Scalar())
 returns the separable linear filter engine
 cv::CV_EXPORTS_AS (floodFillMask) int floodFill(Mat &image
 fills the semi-uniform image region and/or the mask starting from the specified seed point
 cv::CV_EXPORTS_AS (integral3) void integral(const Mat &src
 computes the integral image, integral for the squared image and the tilted integral image
 cv::CV_EXPORTS_AS (integral2) void integral(const Mat &src
 computes the integral image and integral for the squared image
 cv::CV_EXPORTS_AS (houghCircles) void HoughCircles(const Mat &image
 finds circles in the grayscale image using 2+1 gradient Hough transform
 cv::CV_EXPORTS_AS (houghLinesP) void HoughLinesP(Mat &image
 finds line segments in the black-n-white image using probabalistic Hough transform
 cv::CV_EXPORTS_AS (houghLines) void HoughLines(const Mat &image
 finds lines in the black-n-white image using the standard or pyramid Hough transform
 cv::CV_EXPORTS_AS (canny) void Canny(const Mat &image
 applies Canny edge detector and produces the edge map.
 cv::CV_EXPORTS_AS (laplacian) void Laplacian(const Mat &src
 applies Laplacian operator to the image
 cv::CV_EXPORTS_AS (scharr) void Scharr(const Mat &src
 applies the vertical or horizontal Scharr operator to the image
 cv::CV_EXPORTS_AS (sobel) void Sobel(const Mat &src
 applies generalized Sobel operator to the image
 cv::CV_EXPORTS_AS (gaussianBlur) void GaussianBlur(const Mat &src
 smooths the image using Gaussian filter.
CV_EXPORTS_W void cv::cvtColor (const Mat &src, CV_OUT Mat &dst, int code, int dstCn=0)
 converts image from one color space to another
CV_EXPORTS_W void cv::dilate (const Mat &src, CV_OUT Mat &dst, const Mat &kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
 dilates the image (applies the local maximum operator)
CV_EXPORTS_W void cv::distanceTransform (const Mat &src, CV_OUT Mat &dst, int distanceType, int maskSize)
 computes the distance transform map
void cv::distanceTransform (const Mat &src, CV_OUT Mat &dst, Mat &labels, int distanceType, int maskSize)
 builds the discrete Voronoi diagram
void cv::drawContours (Mat &image, const vector< vector< Point > > &contours, int contourIdx, const Scalar &color, int thickness=1, int lineType=8, const vector< Vec4i > &hierarchy=vector< Vec4i >(), int maxLevel=INT_MAX, Point offset=Point())
 draws contours in the image
CV_EXPORTS_W void cv::equalizeHist (const Mat &src, CV_OUT Mat &dst)
 normalizes the grayscale image brightness and contrast by normalizing its histogram
CV_EXPORTS_W void cv::erode (const Mat &src, CV_OUT Mat &dst, const Mat &kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
 erodes the image (applies the local minimum operator)
CV_EXPORTS_W Mat cv::estimateRigidTransform (const Mat &A, const Mat &B, bool fullAffine)
 estimates the best-fit affine transformation that maps one 2D point set to another or one image to another.
CV_EXPORTS_W void cv::filter2D (const Mat &src, CV_OUT Mat &dst, int ddepth, const Mat &kernel, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT)
 applies non-separable 2D linear filter to the image
void cv::findContours (Mat &image, CV_OUT vector< vector< Point > > &contours, int mode, int method, Point offset=Point())
 retrieves contours from black-n-white image.
void cv::findContours (Mat &image, CV_OUT vector< vector< Point > > &contours, vector< Vec4i > &hierarchy, int mode, int method, Point offset=Point())
 retrieves contours and the hierarchical information from black-n-white image.
CV_EXPORTS_W RotatedRect cv::fitEllipse (const Mat &points)
 fits ellipse to the set of 2D points
void cv::fitLine (const Mat &points, CV_OUT Vec4f &line, int distType, double param, double reps, double aeps)
 fits line to the set of 2D points using M-estimator algorithm
CV_EXPORTS_W int cv::floodFill (Mat &image, Point seedPoint, Scalar newVal, CV_OUT Rect *rect=0, Scalar loDiff=Scalar(), Scalar upDiff=Scalar(), int flags=4)
 fills the semi-uniform image region starting from the specified seed point
Mat cv::getAffineTransform (const Point2f src[], const Point2f dst[])
 returns 2x3 affine transformation for the corresponding 3 point pairs.
Ptr< BaseColumnFilter > cv::getColumnSumFilter (int sumType, int dstType, int ksize, int anchor=-1, double scale=1)
 returns vertical 1D box filter
CV_EXPORTS_W Mat cv::getDefaultNewCameraMatrix (const Mat &cameraMatrix, Size imgsize=Size(), bool centerPrincipalPoint=false)
 returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true)
CV_EXPORTS_W void cv::getDerivKernels (CV_OUT Mat &kx, CV_OUT Mat &ky, int dx, int dy, int ksize, bool normalize=false, int ktype=CV_32F)
 initializes kernels of the generalized Sobel operator
CV_EXPORTS_W Mat cv::getGaussianKernel (int ksize, double sigma, int ktype=CV_64F)
 returns the Gaussian kernel with the specified parameters
int cv::getKernelType (const Mat &kernel, Point anchor)
 returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients.
Ptr< BaseColumnFilter > cv::getLinearColumnFilter (int bufType, int dstType, const Mat &kernel, int anchor, int symmetryType, double delta=0, int bits=0)
 returns the primitive column filter with the specified kernel
Ptr< BaseFilter > cv::getLinearFilter (int srcType, int dstType, const Mat &kernel, Point anchor=Point(-1,-1), double delta=0, int bits=0)
 returns 2D filter with the specified kernel
Ptr< BaseRowFilter > cv::getLinearRowFilter (int srcType, int bufType, const Mat &kernel, int anchor, int symmetryType)
 returns the primitive row filter with the specified kernel
Ptr< BaseColumnFilter > cv::getMorphologyColumnFilter (int op, int type, int ksize, int anchor=-1)
 returns vertical 1D morphological filter
Ptr< BaseFilter > cv::getMorphologyFilter (int op, int type, const Mat &kernel, Point anchor=Point(-1,-1))
 returns 2D morphological filter
Ptr< BaseRowFilter > cv::getMorphologyRowFilter (int op, int type, int ksize, int anchor=-1)
 returns horizontal 1D morphological filter
Mat cv::getPerspectiveTransform (const Point2f src[], const Point2f dst[])
 returns 3x3 perspective transformation for the corresponding 4 point pairs.
CV_EXPORTS_W void cv::getRectSubPix (const Mat &image, Size patchSize, Point2f center, CV_OUT Mat &patch, int patchType=-1)
 extracts rectangle from the image at sub-pixel location
CV_EXPORTS_W Mat cv::getRotationMatrix2D (Point2f center, double angle, double scale)
 returns 2x3 affine transformation matrix for the planar rotation.
Ptr< BaseRowFilter > cv::getRowSumFilter (int srcType, int sumType, int ksize, int anchor=-1)
 returns horizontal 1D box filter
CV_EXPORTS_W Mat cv::getStructuringElement (int shape, Size ksize, Point anchor=Point(-1,-1))
 returns structuring element of the specified shape and size
CV_EXPORTS_W void cv::goodFeaturesToTrack (const Mat &image, CV_OUT vector< Point2f > &corners, int maxCorners, double qualityLevel, double minDistance, const Mat &mask=Mat(), int blockSize=3, bool useHarrisDetector=false, double k=0.04)
 finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima
CV_EXPORTS_W void cv::grabCut (const Mat &img, Mat &mask, Rect rect, Mat &bgdModel, Mat &fgdModel, int iterCount, int mode=GC_EVAL)
 segments the image using GrabCut algorithm
void cv::HuMoments (const Moments &moments, double hu[7])
 computes 7 Hu invariants from the moments
CV_EXPORTS_W void cv::initUndistortRectifyMap (const Mat &cameraMatrix, const Mat &distCoeffs, const Mat &R, const Mat &newCameraMatrix, Size size, int m1type, CV_OUT Mat &map1, CV_OUT Mat &map2)
 initializes maps for cv::remap() to correct lens distortion and optionally rectify the image
CV_EXPORTS_W float cv::initWideAngleProjMap (const Mat &cameraMatrix, const Mat &distCoeffs, Size imageSize, int destImageWidth, int m1type, CV_OUT Mat &map1, CV_OUT Mat &map2, int projType=PROJ_SPHERICAL_EQRECT, double alpha=0)
 initializes maps for cv::remap() for wide-angle
CV_EXPORTS_W void cv::inpaint (const Mat &src, const Mat &inpaintMask, CV_OUT Mat &dst, double inpaintRange, int flags)
 restores the damaged image areas using one of the available intpainting algorithms
CV_EXPORTS_W void cv::integral (const Mat &src, CV_OUT Mat &sum, int sdepth=-1)
 computes the integral image
CV_EXPORTS_W void cv::invertAffineTransform (const Mat &M, CV_OUT Mat &iM)
 computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation.
CV_EXPORTS_W bool cv::isContourConvex (const Mat &contour)
 returns true iff the contour is convex. Does not support contours with self-intersection
CV_EXPORTS_W double cv::matchShapes (const Mat &contour1, const Mat &contour2, int method, double parameter)
 matches two contours using one of the available algorithms
CV_EXPORTS_W void cv::matchTemplate (const Mat &image, const Mat &templ, CV_OUT Mat &result, int method)
 computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS_W void cv::medianBlur (const Mat &src, CV_OUT Mat &dst, int ksize)
 smooths the image using median filter.
CV_EXPORTS_W RotatedRect cv::minAreaRect (const Mat &points)
 computes the minimal rotated rectangle for a set of points
CV_EXPORTS_W void cv::minEnclosingCircle (const Mat &points, Point2f &center, float &radius)
 computes the minimal enclosing circle for a set of points
CV_EXPORTS_W Moments cv::moments (const Mat &array, bool binaryImage=false)
 computes moments of the rasterized shape or a vector of points
CV_EXPORTS_W void cv::morphologyEx (const Mat &src, CV_OUT Mat &dst, int op, const Mat &kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
 applies an advanced morphological operation to the image
CV_EXPORTS_W double cv::pointPolygonTest (const Mat &contour, Point2f pt, bool measureDist)
 checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary
CV_EXPORTS_W void cv::preCornerDetect (const Mat &src, CV_OUT Mat &dst, int ksize, int borderType=BORDER_DEFAULT)
 computes another complex cornerness criteria at each pixel
CV_EXPORTS_W void cv::pyrDown (const Mat &src, CV_OUT Mat &dst, const Size &dstsize=Size())
 smooths and downsamples the image
CV_EXPORTS_W void cv::pyrMeanShiftFiltering (const Mat &src, CV_OUT Mat &dst, double sp, double sr, int maxLevel=1, TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1))
 filters image using meanshift algorithm
CV_EXPORTS_W void cv::pyrUp (const Mat &src, CV_OUT Mat &dst, const Size &dstsize=Size())
 upsamples and smoothes the image
CV_EXPORTS_W void cv::remap (const Mat &src, CV_OUT Mat &dst, const Mat &map1, const Mat &map2, int interpolation, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
 warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format
CV_EXPORTS_W void cv::resize (const Mat &src, CV_OUT Mat &dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR)
 resizes the image
CV_EXPORTS_W void cv::sepFilter2D (const Mat &src, CV_OUT Mat &dst, int ddepth, const Mat &kernelX, const Mat &kernelY, Point anchor=Point(-1,-1), double delta=0, int borderType=BORDER_DEFAULT)
 applies separable 2D linear filter to the image
CV_EXPORTS_W double cv::threshold (const Mat &src, CV_OUT Mat &dst, double thresh, double maxval, int type)
 applies fixed threshold to the image
CV_EXPORTS_W void cv::undistort (const Mat &src, CV_OUT Mat &dst, const Mat &cameraMatrix, const Mat &distCoeffs, const Mat &newCameraMatrix=Mat())
 corrects lens distortion for the given camera matrix and distortion coefficients
CV_EXPORTS_W void cv::undistortPoints (const Mat &src, CV_OUT Mat &dst, const Mat &cameraMatrix, const Mat &distCoeffs, const Mat &R=Mat(), const Mat &P=Mat())
 returns points' coordinates after lens distortion correction
void cv::undistortPoints (const Mat &src, CV_OUT vector< Point2f > &dst, const Mat &cameraMatrix, const Mat &distCoeffs, const Mat &R=Mat(), const Mat &P=Mat())
 returns points' coordinates after lens distortion correction
CV_EXPORTS_W void cv::warpAffine (const Mat &src, CV_OUT Mat &dst, const Mat &M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
 warps the image using affine transformation
CV_EXPORTS_W void cv::warpPerspective (const Mat &src, CV_OUT Mat &dst, const Mat &M, Size dsize, int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, const Scalar &borderValue=Scalar())
 warps the image using perspective transformation
CV_EXPORTS_W void cv::watershed (const Mat &image, Mat &markers)
 segments the image using watershed algorithm

Variables

CV_OUT Mat double double int cv::apertureSize = 3
CV_OUT Mat Size double double int cv::borderType = BORDER_DEFAULT )
CV_OUT vector< Vec3f > & cv::circles
CV_OUT Mat int cv::ddepth
CV_OUT Mat int int int int
double double 
cv::delta = 0
CV_OUT vector< Vec3f > int double cv::dp
CV_OUT Mat & cv::dst
CV_OUT Mat int int cv::dx
CV_OUT Mat int int int cv::dy
CV_OUT Mat & cv::edges
Mat Point Scalar CV_OUT Rect
Scalar Scalar int 
cv::flags = 4 )
CV_OUT Mat Size cv::ksize = 3
CV_OUT Mat double double int bool cv::L2gradient = false )
CV_OUT vector< Vec2f > & cv::lines
Mat Point Scalar CV_OUT Rect Scalar cv::loDiff = Scalar()
Mat & cv::mask
CV_OUT vector< Vec4i > double
double int double double 
cv::maxLineGap = 0 )
CV_OUT vector< Vec3f > int
double double double double
int int 
cv::maxRadius = 0 )
CV_OUT vector< Vec3f > int cv::method = 0
CV_OUT vector< Vec3f > int
double double 
cv::minDist
CV_OUT vector< Vec4i > double
double int double 
cv::minLineLength = 0
CV_OUT vector< Vec3f > int
double double double double
int 
cv::minRadius = 0
Mat Point Scalar cv::newVal
CV_OUT vector< Vec3f > int
double double double 
cv::param1 = 100
CV_OUT vector< Vec3f > int
double double double double 
cv::param2 = 100
Mat Point Scalar CV_OUT Rect * cv::rect = 0
CV_OUT vector< Vec2f > double cv::rho
CV_OUT Mat int int int int double cv::scale = 1
CV_OUT Mat CV_OUT Mat int cv::sdepth = -1 )
Mat Point cv::seedPoint
CV_OUT Mat Size double cv::sigma1
CV_OUT Mat Size double double cv::sigma2 = 0
CV_OUT Mat CV_OUT Mat & cv::sqsum
CV_OUT vector< Vec2f > double
double int double 
cv::srn = 0
CV_OUT vector< Vec2f > double
double int double double 
cv::stn = 0 )
CV_OUT Mat & cv::sum
CV_OUT vector< Vec2f > double
double 
cv::theta
CV_OUT vector< Vec2f > double
double int 
cv::threshold
CV_OUT Mat double cv::threshold1
CV_OUT Mat double double cv::threshold2
CV_OUT Mat CV_OUT Mat CV_OUT Mat & cv::tilted
Mat Point Scalar CV_OUT Rect
Scalar Scalar 
cv::upDiff = Scalar()

Detailed Description

The Image Processing.

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