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+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef __OPENCV_IMGPROC_HPP__
+#define __OPENCV_IMGPROC_HPP__
+
+#include "opencv2/core/core.hpp"
+#include "opencv2/imgproc/types_c.h"
+
+#ifdef __cplusplus
+
+/*! \namespace cv
+ Namespace where all the C++ OpenCV functionality resides
+ */
+namespace cv
+{
+
+//! various border interpolation methods
+enum { BORDER_REPLICATE=IPL_BORDER_REPLICATE, BORDER_CONSTANT=IPL_BORDER_CONSTANT,
+       BORDER_REFLECT=IPL_BORDER_REFLECT, BORDER_WRAP=IPL_BORDER_WRAP,
+       BORDER_REFLECT_101=IPL_BORDER_REFLECT_101, BORDER_REFLECT101=BORDER_REFLECT_101,
+       BORDER_TRANSPARENT=IPL_BORDER_TRANSPARENT,
+       BORDER_DEFAULT=BORDER_REFLECT_101, BORDER_ISOLATED=16 };
+
+//! 1D interpolation function: returns coordinate of the "donor" pixel for the specified location p.
+CV_EXPORTS_W int borderInterpolate( int p, int len, int borderType );
+
+/*!
+ The Base Class for 1D or Row-wise Filters
+
+ This is the base class for linear or non-linear filters that process 1D data.
+ In particular, such filters are used for the "horizontal" filtering parts in separable filters.
+
+ Several functions in OpenCV return Ptr<BaseRowFilter> for the specific types of filters,
+ and those pointers can be used directly or within cv::FilterEngine.
+*/
+class CV_EXPORTS BaseRowFilter
+{
+public:
+    //! the default constructor
+    BaseRowFilter();
+    //! the destructor
+    virtual ~BaseRowFilter();
+    //! the filtering operator. Must be overridden in the derived classes. The horizontal border interpolation is done outside of the class.
+    virtual void operator()(const uchar* src, uchar* dst,
+                            int width, int cn) = 0;
+    int ksize, anchor;
+};
+
+
+/*!
+ The Base Class for Column-wise Filters
+
+ This is the base class for linear or non-linear filters that process columns of 2D arrays.
+ Such filters are used for the "vertical" filtering parts in separable filters.
+
+ Several functions in OpenCV return Ptr<BaseColumnFilter> for the specific types of filters,
+ and those pointers can be used directly or within cv::FilterEngine.
+
+ Unlike cv::BaseRowFilter, cv::BaseColumnFilter may have some context information,
+ i.e. box filter keeps the sliding sum of elements. To reset the state BaseColumnFilter::reset()
+ must be called (e.g. the method is called by cv::FilterEngine)
+ */
+class CV_EXPORTS BaseColumnFilter
+{
+public:
+    //! the default constructor
+    BaseColumnFilter();
+    //! the destructor
+    virtual ~BaseColumnFilter();
+    //! the filtering operator. Must be overridden in the derived classes. The vertical border interpolation is done outside of the class.
+    virtual void operator()(const uchar** src, uchar* dst, int dststep,
+                            int dstcount, int width) = 0;
+    //! resets the internal buffers, if any
+    virtual void reset();
+    int ksize, anchor;
+};
+
+/*!
+ The Base Class for Non-Separable 2D Filters.
+
+ This is the base class for linear or non-linear 2D filters.
+
+ Several functions in OpenCV return Ptr<BaseFilter> for the specific types of filters,
+ and those pointers can be used directly or within cv::FilterEngine.
+
+ Similar to cv::BaseColumnFilter, the class may have some context information,
+ that should be reset using BaseFilter::reset() method before processing the new array.
+*/
+class CV_EXPORTS BaseFilter
+{
+public:
+    //! the default constructor
+    BaseFilter();
+    //! the destructor
+    virtual ~BaseFilter();
+    //! the filtering operator. The horizontal and the vertical border interpolation is done outside of the class.
+    virtual void operator()(const uchar** src, uchar* dst, int dststep,
+                            int dstcount, int width, int cn) = 0;
+    //! resets the internal buffers, if any
+    virtual void reset();
+    Size ksize;
+    Point anchor;
+};
+
+/*!
+ The Main Class for Image Filtering.
+
+ The class can be used to apply an arbitrary filtering operation to an image.
+ It contains all the necessary intermediate buffers, it computes extrapolated values
+ of the "virtual" pixels outside of the image etc.
+ Pointers to the initialized cv::FilterEngine instances
+ are returned by various OpenCV functions, such as cv::createSeparableLinearFilter(),
+ cv::createLinearFilter(), cv::createGaussianFilter(), cv::createDerivFilter(),
+ cv::createBoxFilter() and cv::createMorphologyFilter().
+
+ Using the class you can process large images by parts and build complex pipelines
+ that include filtering as some of the stages. If all you need is to apply some pre-defined
+ filtering operation, you may use cv::filter2D(), cv::erode(), cv::dilate() etc.
+ functions that create FilterEngine internally.
+
+ Here is the example on how to use the class to implement Laplacian operator, which is the sum of
+ second-order derivatives. More complex variant for different types is implemented in cv::Laplacian().
+
+ \code
+ void laplace_f(const Mat& src, Mat& dst)
+ {
+     CV_Assert( src.type() == CV_32F );
+     // make sure the destination array has the proper size and type
+     dst.create(src.size(), src.type());
+
+     // get the derivative and smooth kernels for d2I/dx2.
+     // for d2I/dy2 we could use the same kernels, just swapped
+     Mat kd, ks;
+     getSobelKernels( kd, ks, 2, 0, ksize, false, ktype );
+
+     // let's process 10 source rows at once
+     int DELTA = std::min(10, src.rows);
+     Ptr<FilterEngine> Fxx = createSeparableLinearFilter(src.type(),
+     dst.type(), kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
+     Ptr<FilterEngine> Fyy = createSeparableLinearFilter(src.type(),
+     dst.type(), ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );
+
+     int y = Fxx->start(src), dsty = 0, dy = 0;
+     Fyy->start(src);
+     const uchar* sptr = src.data + y*src.step;
+
+     // allocate the buffers for the spatial image derivatives;
+     // the buffers need to have more than DELTA rows, because at the
+     // last iteration the output may take max(kd.rows-1,ks.rows-1)
+     // rows more than the input.
+     Mat Ixx( DELTA + kd.rows - 1, src.cols, dst.type() );
+     Mat Iyy( DELTA + kd.rows - 1, src.cols, dst.type() );
+
+     // inside the loop we always pass DELTA rows to the filter
+     // (note that the "proceed" method takes care of possibe overflow, since
+     // it was given the actual image height in the "start" method)
+     // on output we can get:
+     //  * < DELTA rows (the initial buffer accumulation stage)
+     //  * = DELTA rows (settled state in the middle)
+     //  * > DELTA rows (then the input image is over, but we generate
+     //                  "virtual" rows using the border mode and filter them)
+     // this variable number of output rows is dy.
+     // dsty is the current output row.
+     // sptr is the pointer to the first input row in the portion to process
+     for( ; dsty < dst.rows; sptr += DELTA*src.step, dsty += dy )
+     {
+         Fxx->proceed( sptr, (int)src.step, DELTA, Ixx.data, (int)Ixx.step );
+         dy = Fyy->proceed( sptr, (int)src.step, DELTA, d2y.data, (int)Iyy.step );
+         if( dy > 0 )
+         {
+             Mat dstripe = dst.rowRange(dsty, dsty + dy);
+             add(Ixx.rowRange(0, dy), Iyy.rowRange(0, dy), dstripe);
+         }
+     }
+ }
+ \endcode
+*/
+class CV_EXPORTS FilterEngine
+{
+public:
+    //! the default constructor
+    FilterEngine();
+    //! the full constructor. Either _filter2D or both _rowFilter and _columnFilter must be non-empty.
+    FilterEngine(const Ptr<BaseFilter>& _filter2D,
+                 const Ptr<BaseRowFilter>& _rowFilter,
+                 const Ptr<BaseColumnFilter>& _columnFilter,
+                 int srcType, int dstType, int bufType,
+                 int _rowBorderType=BORDER_REPLICATE,
+                 int _columnBorderType=-1,
+                 const Scalar& _borderValue=Scalar());
+    //! the destructor
+    virtual ~FilterEngine();
+    //! reinitializes the engine. The previously assigned filters are released.
+    void init(const Ptr<BaseFilter>& _filter2D,
+              const Ptr<BaseRowFilter>& _rowFilter,
+              const Ptr<BaseColumnFilter>& _columnFilter,
+              int srcType, int dstType, int bufType,
+              int _rowBorderType=BORDER_REPLICATE, int _columnBorderType=-1,
+              const Scalar& _borderValue=Scalar());
+    //! starts filtering of the specified ROI of an image of size wholeSize.
+    virtual int start(Size wholeSize, Rect roi, int maxBufRows=-1);
+    //! starts filtering of the specified ROI of the specified image.
+    virtual int start(const Mat& src, const Rect& srcRoi=Rect(0,0,-1,-1),
+                      bool isolated=false, int maxBufRows=-1);
+    //! processes the next srcCount rows of the image.
+    virtual int proceed(const uchar* src, int srcStep, int srcCount,
+                        uchar* dst, int dstStep);
+    //! applies filter to the specified ROI of the image. if srcRoi=(0,0,-1,-1), the whole image is filtered.
+    virtual void apply( const Mat& src, Mat& dst,
+                        const Rect& srcRoi=Rect(0,0,-1,-1),
+                        Point dstOfs=Point(0,0),
+                        bool isolated=false);
+    //! returns true if the filter is separable
+    bool isSeparable() const { return (const BaseFilter*)filter2D == 0; }
+    //! returns the number
+    int remainingInputRows() const;
+    int remainingOutputRows() const;
+
+    int srcType, dstType, bufType;
+    Size ksize;
+    Point anchor;
+    int maxWidth;
+    Size wholeSize;
+    Rect roi;
+    int dx1, dx2;
+    int rowBorderType, columnBorderType;
+    vector<int> borderTab;
+    int borderElemSize;
+    vector<uchar> ringBuf;
+    vector<uchar> srcRow;
+    vector<uchar> constBorderValue;
+    vector<uchar> constBorderRow;
+    int bufStep, startY, startY0, endY, rowCount, dstY;
+    vector<uchar*> rows;
+
+    Ptr<BaseFilter> filter2D;
+    Ptr<BaseRowFilter> rowFilter;
+    Ptr<BaseColumnFilter> columnFilter;
+};
+
+//! type of the kernel
+enum { KERNEL_GENERAL=0, KERNEL_SYMMETRICAL=1, KERNEL_ASYMMETRICAL=2,
+       KERNEL_SMOOTH=4, KERNEL_INTEGER=8 };
+
+//! returns type (one of KERNEL_*) of 1D or 2D kernel specified by its coefficients.
+CV_EXPORTS int getKernelType(InputArray kernel, Point anchor);
+
+//! returns the primitive row filter with the specified kernel
+CV_EXPORTS Ptr<BaseRowFilter> getLinearRowFilter(int srcType, int bufType,
+                                            InputArray kernel, int anchor,
+                                            int symmetryType);
+
+//! returns the primitive column filter with the specified kernel
+CV_EXPORTS Ptr<BaseColumnFilter> getLinearColumnFilter(int bufType, int dstType,
+                                            InputArray kernel, int anchor,
+                                            int symmetryType, double delta=0,
+                                            int bits=0);
+
+//! returns 2D filter with the specified kernel
+CV_EXPORTS Ptr<BaseFilter> getLinearFilter(int srcType, int dstType,
+                                           InputArray kernel,
+                                           Point anchor=Point(-1,-1),
+                                           double delta=0, int bits=0);
+
+//! returns the separable linear filter engine
+CV_EXPORTS Ptr<FilterEngine> createSeparableLinearFilter(int srcType, int dstType,
+                          InputArray rowKernel, InputArray columnKernel,
+                          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
+CV_EXPORTS Ptr<FilterEngine> createLinearFilter(int srcType, int dstType,
+                 InputArray kernel, Point _anchor=Point(-1,-1),
+                 double delta=0, int rowBorderType=BORDER_DEFAULT,
+                 int columnBorderType=-1, const Scalar& borderValue=Scalar());
+
+//! returns the Gaussian kernel with the specified parameters
+CV_EXPORTS_W Mat getGaussianKernel( int ksize, double sigma, int ktype=CV_64F );
+
+//! returns the Gaussian filter engine
+CV_EXPORTS Ptr<FilterEngine> createGaussianFilter( int type, Size ksize,
+                                    double sigma1, double sigma2=0,
+                                    int borderType=BORDER_DEFAULT);
+//! initializes kernels of the generalized Sobel operator
+CV_EXPORTS_W void getDerivKernels( OutputArray kx, OutputArray ky,
+                                   int dx, int dy, int ksize,
+                                   bool normalize=false, int ktype=CV_32F );
+//! returns filter engine for the generalized Sobel operator
+CV_EXPORTS Ptr<FilterEngine> createDerivFilter( int srcType, int dstType,
+                                        int dx, int dy, int ksize,
+                                        int borderType=BORDER_DEFAULT );
+//! returns horizontal 1D box filter
+CV_EXPORTS Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType,
+                                              int ksize, int anchor=-1);
+//! returns vertical 1D box filter
+CV_EXPORTS Ptr<BaseColumnFilter> getColumnSumFilter( int sumType, int dstType,
+                                                     int ksize, int anchor=-1,
+                                                     double scale=1);
+//! returns box filter engine
+CV_EXPORTS Ptr<FilterEngine> createBoxFilter( int srcType, int dstType, Size ksize,
+                                              Point anchor=Point(-1,-1),
+                                              bool normalize=true,
+                                              int borderType=BORDER_DEFAULT);
+
+//! returns the Gabor kernel with the specified parameters
+CV_EXPORTS_W Mat getGaborKernel( Size ksize, double sigma, double theta, double lambd,
+                                 double gamma, double psi=CV_PI*0.5, int ktype=CV_64F );
+
+//! type of morphological operation
+enum { MORPH_ERODE=CV_MOP_ERODE, MORPH_DILATE=CV_MOP_DILATE,
+       MORPH_OPEN=CV_MOP_OPEN, MORPH_CLOSE=CV_MOP_CLOSE,
+       MORPH_GRADIENT=CV_MOP_GRADIENT, MORPH_TOPHAT=CV_MOP_TOPHAT,
+       MORPH_BLACKHAT=CV_MOP_BLACKHAT, MORPH_HITMISS };
+
+//! returns horizontal 1D morphological filter
+CV_EXPORTS Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize, int anchor=-1);
+//! returns vertical 1D morphological filter
+CV_EXPORTS Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor=-1);
+//! returns 2D morphological filter
+CV_EXPORTS Ptr<BaseFilter> getMorphologyFilter(int op, int type, InputArray kernel,
+                                               Point anchor=Point(-1,-1));
+
+//! returns "magic" border value for erosion and dilation. It is automatically transformed to Scalar::all(-DBL_MAX) for dilation.
+static inline Scalar morphologyDefaultBorderValue() { return Scalar::all(DBL_MAX); }
+
+//! returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported.
+CV_EXPORTS Ptr<FilterEngine> createMorphologyFilter(int op, int type, InputArray kernel,
+                    Point anchor=Point(-1,-1), int rowBorderType=BORDER_CONSTANT,
+                    int columnBorderType=-1,
+                    const Scalar& borderValue=morphologyDefaultBorderValue());
+
+//! shape of the structuring element
+enum { MORPH_RECT=0, MORPH_CROSS=1, MORPH_ELLIPSE=2 };
+//! returns structuring element of the specified shape and size
+CV_EXPORTS_W Mat getStructuringElement(int shape, Size ksize, Point anchor=Point(-1,-1));
+
+template<> CV_EXPORTS void Ptr<IplConvKernel>::delete_obj();
+
+//! 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 copyMakeBorder( InputArray src, OutputArray dst,
+                                int top, int bottom, int left, int right,
+                                int borderType, const Scalar& value=Scalar() );
+
+//! smooths the image using median filter.
+CV_EXPORTS_W void medianBlur( InputArray src, OutputArray dst, int ksize );
+//! smooths the image using Gaussian filter.
+CV_EXPORTS_W void GaussianBlur( InputArray src,
+                                               OutputArray dst, Size ksize,
+                                               double sigmaX, double sigmaY=0,
+                                               int borderType=BORDER_DEFAULT );
+//! smooths the image using bilateral filter
+CV_EXPORTS_W void bilateralFilter( InputArray src, OutputArray dst, int d,
+                                   double sigmaColor, double sigmaSpace,
+                                   int borderType=BORDER_DEFAULT );
+//! smooths the image using adaptive bilateral filter
+CV_EXPORTS_W void adaptiveBilateralFilter( InputArray src, OutputArray dst, Size ksize,
+                                           double sigmaSpace, double maxSigmaColor = 20.0, Point anchor=Point(-1, -1),
+                                           int borderType=BORDER_DEFAULT );
+//! smooths the image using the box filter. Each pixel is processed in O(1) time
+CV_EXPORTS_W void boxFilter( InputArray src, OutputArray dst, int ddepth,
+                             Size ksize, Point anchor=Point(-1,-1),
+                             bool normalize=true,
+                             int borderType=BORDER_DEFAULT );
+//! a synonym for normalized box filter
+CV_EXPORTS_W void blur( InputArray src, OutputArray dst,
+                        Size ksize, Point anchor=Point(-1,-1),
+                        int borderType=BORDER_DEFAULT );
+
+//! applies non-separable 2D linear filter to the image
+CV_EXPORTS_W void filter2D( InputArray src, OutputArray dst, int ddepth,
+                            InputArray kernel, Point anchor=Point(-1,-1),
+                            double delta=0, int borderType=BORDER_DEFAULT );
+
+//! applies separable 2D linear filter to the image
+CV_EXPORTS_W void sepFilter2D( InputArray src, OutputArray dst, int ddepth,
+                               InputArray kernelX, InputArray kernelY,
+                               Point anchor=Point(-1,-1),
+                               double delta=0, int borderType=BORDER_DEFAULT );
+
+//! applies generalized Sobel operator to the image
+CV_EXPORTS_W void Sobel( InputArray src, OutputArray dst, int ddepth,
+                         int dx, int dy, int ksize=3,
+                         double scale=1, double delta=0,
+                         int borderType=BORDER_DEFAULT );
+
+//! applies the vertical or horizontal Scharr operator to the image
+CV_EXPORTS_W void Scharr( InputArray src, OutputArray dst, int ddepth,
+                          int dx, int dy, double scale=1, double delta=0,
+                          int borderType=BORDER_DEFAULT );
+
+//! applies Laplacian operator to the image
+CV_EXPORTS_W void Laplacian( InputArray src, OutputArray dst, int ddepth,
+                             int ksize=1, double scale=1, double delta=0,
+                             int borderType=BORDER_DEFAULT );
+
+//! applies Canny edge detector and produces the edge map.
+CV_EXPORTS_W void Canny( InputArray image, OutputArray edges,
+                         double threshold1, double threshold2,
+                         int apertureSize=3, bool L2gradient=false );
+
+//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
+CV_EXPORTS_W void cornerMinEigenVal( InputArray src, OutputArray dst,
+                                   int blockSize, int ksize=3,
+                                   int borderType=BORDER_DEFAULT );
+
+//! computes Harris cornerness criteria at each image pixel
+CV_EXPORTS_W void cornerHarris( InputArray src, OutputArray dst, int blockSize,
+                                int ksize, double k,
+                                int borderType=BORDER_DEFAULT );
+
+// low-level function for computing eigenvalues and eigenvectors of 2x2 matrices
+CV_EXPORTS void eigen2x2( const float* a, float* e, int n );
+
+//! 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 cornerEigenValsAndVecs( InputArray src, OutputArray dst,
+                                          int blockSize, int ksize,
+                                          int borderType=BORDER_DEFAULT );
+
+//! computes another complex cornerness criteria at each pixel
+CV_EXPORTS_W void preCornerDetect( InputArray src, OutputArray dst, int ksize,
+                                   int borderType=BORDER_DEFAULT );
+
+//! adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria
+CV_EXPORTS_W void cornerSubPix( InputArray image, InputOutputArray corners,
+                                Size winSize, Size zeroZone,
+                                TermCriteria criteria );
+
+//! finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima
+CV_EXPORTS_W void goodFeaturesToTrack( InputArray image, OutputArray corners,
+                                     int maxCorners, double qualityLevel, double minDistance,
+                                     InputArray mask=noArray(), int blockSize=3,
+                                     bool useHarrisDetector=false, double k=0.04 );
+
+//! finds lines in the black-n-white image using the standard or pyramid Hough transform
+CV_EXPORTS_W void HoughLines( InputArray image, OutputArray lines,
+                              double rho, double theta, int threshold,
+                              double srn=0, double stn=0 );
+
+//! finds line segments in the black-n-white image using probabilistic Hough transform
+CV_EXPORTS_W void HoughLinesP( InputArray image, OutputArray lines,
+                               double rho, double theta, int threshold,
+                               double minLineLength=0, double maxLineGap=0 );
+
+//! finds circles in the grayscale image using 2+1 gradient Hough transform
+CV_EXPORTS_W void HoughCircles( InputArray image, OutputArray circles,
+                               int method, double dp, double minDist,
+                               double param1=100, double param2=100,
+                               int minRadius=0, int maxRadius=0 );
+
+enum
+{
+    GHT_POSITION = 0,
+    GHT_SCALE = 1,
+    GHT_ROTATION = 2
+};
+
+//! finds arbitrary template in the grayscale image using Generalized Hough Transform
+//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
+//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
+class CV_EXPORTS GeneralizedHough : public Algorithm
+{
+public:
+    static Ptr<GeneralizedHough> create(int method);
+
+    virtual ~GeneralizedHough();
+
+    //! set template to search
+    void setTemplate(InputArray templ, int cannyThreshold = 100, Point templCenter = Point(-1, -1));
+    void setTemplate(InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1));
+
+    //! find template on image
+    void detect(InputArray image, OutputArray positions, OutputArray votes = cv::noArray(), int cannyThreshold = 100);
+    void detect(InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes = cv::noArray());
+
+    void release();
+
+protected:
+    virtual void setTemplateImpl(const Mat& edges, const Mat& dx, const Mat& dy, Point templCenter) = 0;
+    virtual void detectImpl(const Mat& edges, const Mat& dx, const Mat& dy, OutputArray positions, OutputArray votes) = 0;
+    virtual void releaseImpl() = 0;
+
+private:
+    Mat edges_, dx_, dy_;
+};
+
+//! erodes the image (applies the local minimum operator)
+CV_EXPORTS_W void erode( InputArray src, OutputArray dst, InputArray 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 dilate( InputArray src, OutputArray dst, InputArray 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 void morphologyEx( InputArray src, OutputArray dst,
+                                int op, InputArray kernel,
+                                Point anchor=Point(-1,-1), int iterations=1,
+                                int borderType=BORDER_CONSTANT,
+                                const Scalar& borderValue=morphologyDefaultBorderValue() );
+
+//! interpolation algorithm
+enum
+{
+    INTER_NEAREST=CV_INTER_NN, //!< nearest neighbor interpolation
+    INTER_LINEAR=CV_INTER_LINEAR, //!< bilinear interpolation
+    INTER_CUBIC=CV_INTER_CUBIC, //!< bicubic interpolation
+    INTER_AREA=CV_INTER_AREA, //!< area-based (or super) interpolation
+    INTER_LANCZOS4=CV_INTER_LANCZOS4, //!< Lanczos interpolation over 8x8 neighborhood
+    INTER_MAX=7,
+    WARP_INVERSE_MAP=CV_WARP_INVERSE_MAP
+};
+
+//! resizes the image
+CV_EXPORTS_W void resize( InputArray src, OutputArray dst,
+                          Size dsize, double fx=0, double fy=0,
+                          int interpolation=INTER_LINEAR );
+
+//! warps the image using affine transformation
+CV_EXPORTS_W void warpAffine( InputArray src, OutputArray dst,
+                              InputArray 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 warpPerspective( InputArray src, OutputArray dst,
+                                   InputArray M, Size dsize,
+                                   int flags=INTER_LINEAR,
+                                   int borderMode=BORDER_CONSTANT,
+                                   const Scalar& borderValue=Scalar());
+
+enum
+{
+    INTER_BITS=5, INTER_BITS2=INTER_BITS*2,
+    INTER_TAB_SIZE=(1<<INTER_BITS),
+    INTER_TAB_SIZE2=INTER_TAB_SIZE*INTER_TAB_SIZE
+};
+
+//! warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format
+CV_EXPORTS_W void remap( InputArray src, OutputArray dst,
+                         InputArray map1, InputArray map2,
+                         int interpolation, int borderMode=BORDER_CONSTANT,
+                         const Scalar& borderValue=Scalar());
+
+//! converts maps for remap from floating-point to fixed-point format or backwards
+CV_EXPORTS_W void convertMaps( InputArray map1, InputArray map2,
+                               OutputArray dstmap1, OutputArray dstmap2,
+                               int dstmap1type, bool nninterpolation=false );
+
+//! returns 2x3 affine transformation matrix for the planar rotation.
+CV_EXPORTS_W Mat getRotationMatrix2D( Point2f center, double angle, double scale );
+//! returns 3x3 perspective transformation for the corresponding 4 point pairs.
+CV_EXPORTS Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] );
+//! returns 2x3 affine transformation for the corresponding 3 point pairs.
+CV_EXPORTS Mat getAffineTransform( const Point2f src[], const Point2f dst[] );
+//! computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation.
+CV_EXPORTS_W void invertAffineTransform( InputArray M, OutputArray iM );
+
+CV_EXPORTS_W Mat getPerspectiveTransform( InputArray src, InputArray dst );
+CV_EXPORTS_W Mat getAffineTransform( InputArray src, InputArray dst );
+
+//! extracts rectangle from the image at sub-pixel location
+CV_EXPORTS_W void getRectSubPix( InputArray image, Size patchSize,
+                                 Point2f center, OutputArray patch, int patchType=-1 );
+
+//! computes the integral image
+CV_EXPORTS_W void integral( InputArray src, OutputArray sum, int sdepth=-1 );
+
+//! computes the integral image and integral for the squared image
+CV_EXPORTS_AS(integral2) void integral( InputArray src, OutputArray sum,
+                                        OutputArray sqsum, int sdepth=-1 );
+//! computes the integral image, integral for the squared image and the tilted integral image
+CV_EXPORTS_AS(integral3) void integral( InputArray src, OutputArray sum,
+                                        OutputArray sqsum, OutputArray tilted,
+                                        int sdepth=-1 );
+
+//! adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types.
+CV_EXPORTS_W void accumulate( InputArray src, InputOutputArray dst,
+                              InputArray mask=noArray() );
+//! adds squared src image to the accumulator (dst += src*src).
+CV_EXPORTS_W void accumulateSquare( InputArray src, InputOutputArray dst,
+                                    InputArray mask=noArray() );
+//! adds product of the 2 images to the accumulator (dst += src1*src2).
+CV_EXPORTS_W void accumulateProduct( InputArray src1, InputArray src2,
+                                     InputOutputArray dst, InputArray mask=noArray() );
+//! updates the running average (dst = dst*(1-alpha) + src*alpha)
+CV_EXPORTS_W void accumulateWeighted( InputArray src, InputOutputArray dst,
+                                      double alpha, InputArray mask=noArray() );
+
+//! computes PSNR image/video quality metric
+CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2);
+
+CV_EXPORTS_W Point2d phaseCorrelate(InputArray src1, InputArray src2,
+                                  InputArray window = noArray());
+CV_EXPORTS_W Point2d phaseCorrelateRes(InputArray src1, InputArray src2,
+                                    InputArray window, CV_OUT double* response = 0);
+CV_EXPORTS_W void createHanningWindow(OutputArray dst, Size winSize, int type);
+
+//! type of the threshold operation
+enum { THRESH_BINARY=CV_THRESH_BINARY, THRESH_BINARY_INV=CV_THRESH_BINARY_INV,
+       THRESH_TRUNC=CV_THRESH_TRUNC, THRESH_TOZERO=CV_THRESH_TOZERO,
+       THRESH_TOZERO_INV=CV_THRESH_TOZERO_INV, THRESH_MASK=CV_THRESH_MASK,
+       THRESH_OTSU=CV_THRESH_OTSU };
+
+//! applies fixed threshold to the image
+CV_EXPORTS_W double threshold( InputArray src, OutputArray dst,
+                               double thresh, double maxval, int type );
+
+//! adaptive threshold algorithm
+enum { ADAPTIVE_THRESH_MEAN_C=0, ADAPTIVE_THRESH_GAUSSIAN_C=1 };
+
+//! applies variable (adaptive) threshold to the image
+CV_EXPORTS_W void adaptiveThreshold( InputArray src, OutputArray dst,
+                                     double maxValue, int adaptiveMethod,
+                                     int thresholdType, int blockSize, double C );
+
+//! smooths and downsamples the image
+CV_EXPORTS_W void pyrDown( InputArray src, OutputArray dst,
+                           const Size& dstsize=Size(), int borderType=BORDER_DEFAULT );
+//! upsamples and smoothes the image
+CV_EXPORTS_W void pyrUp( InputArray src, OutputArray dst,
+                         const Size& dstsize=Size(), int borderType=BORDER_DEFAULT );
+
+//! builds the gaussian pyramid using pyrDown() as a basic operation
+CV_EXPORTS void buildPyramid( InputArray src, OutputArrayOfArrays dst,
+                              int maxlevel, int borderType=BORDER_DEFAULT );
+
+//! corrects lens distortion for the given camera matrix and distortion coefficients
+CV_EXPORTS_W void undistort( InputArray src, OutputArray dst,
+                             InputArray cameraMatrix,
+                             InputArray distCoeffs,
+                             InputArray newCameraMatrix=noArray() );
+
+//! initializes maps for cv::remap() to correct lens distortion and optionally rectify the image
+CV_EXPORTS_W void initUndistortRectifyMap( InputArray cameraMatrix, InputArray distCoeffs,
+                           InputArray R, InputArray newCameraMatrix,
+                           Size size, int m1type, OutputArray map1, OutputArray map2 );
+
+enum
+{
+    PROJ_SPHERICAL_ORTHO = 0,
+    PROJ_SPHERICAL_EQRECT = 1
+};
+
+//! initializes maps for cv::remap() for wide-angle
+CV_EXPORTS_W float initWideAngleProjMap( InputArray cameraMatrix, InputArray distCoeffs,
+                                         Size imageSize, int destImageWidth,
+                                         int m1type, OutputArray map1, OutputArray map2,
+                                         int projType=PROJ_SPHERICAL_EQRECT, double alpha=0);
+
+//! returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true)
+CV_EXPORTS_W Mat getDefaultNewCameraMatrix( InputArray cameraMatrix, Size imgsize=Size(),
+                                            bool centerPrincipalPoint=false );
+
+//! returns points' coordinates after lens distortion correction
+CV_EXPORTS_W void undistortPoints( InputArray src, OutputArray dst,
+                                   InputArray cameraMatrix, InputArray distCoeffs,
+                                   InputArray R=noArray(), InputArray P=noArray());
+
+template<> CV_EXPORTS void Ptr<CvHistogram>::delete_obj();
+
+//! computes the joint dense histogram for a set of images.
+CV_EXPORTS void calcHist( const Mat* images, int nimages,
+                          const int* channels, InputArray mask,
+                          OutputArray 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.
+CV_EXPORTS void calcHist( const Mat* images, int nimages,
+                          const int* channels, InputArray mask,
+                          SparseMat& hist, int dims,
+                          const int* histSize, const float** ranges,
+                          bool uniform=true, bool accumulate=false );
+
+CV_EXPORTS_W void calcHist( InputArrayOfArrays images,
+                            const vector<int>& channels,
+                            InputArray mask, OutputArray hist,
+                            const vector<int>& histSize,
+                            const vector<float>& ranges,
+                            bool accumulate=false );
+
+//! computes back projection for the set of images
+CV_EXPORTS void calcBackProject( const Mat* images, int nimages,
+                                 const int* channels, InputArray hist,
+                                 OutputArray backProject, const float** ranges,
+                                 double scale=1, bool uniform=true );
+
+//! computes back projection for the set of images
+CV_EXPORTS void calcBackProject( const Mat* images, int nimages,
+                                 const int* channels, const SparseMat& hist,
+                                 OutputArray backProject, const float** ranges,
+                                 double scale=1, bool uniform=true );
+
+CV_EXPORTS_W void calcBackProject( InputArrayOfArrays images, const vector<int>& channels,
+                                   InputArray hist, OutputArray dst,
+                                   const vector<float>& ranges,
+                                   double scale );
+
+/*CV_EXPORTS void calcBackProjectPatch( const Mat* images, int nimages, const int* channels,
+                                      InputArray hist, OutputArray dst, Size patchSize,
+                                      int method, double factor=1 );
+
+CV_EXPORTS_W void calcBackProjectPatch( InputArrayOfArrays images, const vector<int>& channels,
+                                        InputArray hist, OutputArray dst, Size patchSize,
+                                        int method, double factor=1 );*/
+
+//! compares two histograms stored in dense arrays
+CV_EXPORTS_W double compareHist( InputArray H1, InputArray H2, int method );
+
+//! compares two histograms stored in sparse arrays
+CV_EXPORTS double compareHist( const SparseMat& H1, const SparseMat& H2, int method );
+
+//! normalizes the grayscale image brightness and contrast by normalizing its histogram
+CV_EXPORTS_W void equalizeHist( InputArray src, OutputArray dst );
+
+class CV_EXPORTS_W CLAHE : public Algorithm
+{
+public:
+    CV_WRAP virtual void apply(InputArray src, OutputArray dst) = 0;
+
+    CV_WRAP virtual void setClipLimit(double clipLimit) = 0;
+    CV_WRAP virtual double getClipLimit() const = 0;
+
+    CV_WRAP virtual void setTilesGridSize(Size tileGridSize) = 0;
+    CV_WRAP virtual Size getTilesGridSize() const = 0;
+
+    CV_WRAP virtual void collectGarbage() = 0;
+};
+CV_EXPORTS_W Ptr<CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
+
+CV_EXPORTS float EMD( InputArray signature1, InputArray signature2,
+                      int distType, InputArray cost=noArray(),
+                      float* lowerBound=0, OutputArray flow=noArray() );
+
+//! segments the image using watershed algorithm
+CV_EXPORTS_W void watershed( InputArray image, InputOutputArray markers );
+
+//! filters image using meanshift algorithm
+CV_EXPORTS_W void pyrMeanShiftFiltering( InputArray src, OutputArray dst,
+                                         double sp, double sr, int maxLevel=1,
+                                         TermCriteria termcrit=TermCriteria(
+                                            TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) );
+
+//! class of the pixel in GrabCut algorithm
+enum
+{
+    GC_BGD    = 0,  //!< background
+    GC_FGD    = 1,  //!< foreground
+    GC_PR_BGD = 2,  //!< most probably background
+    GC_PR_FGD = 3   //!< most probably foreground
+};
+
+//! GrabCut algorithm flags
+enum
+{
+    GC_INIT_WITH_RECT  = 0,
+    GC_INIT_WITH_MASK  = 1,
+    GC_EVAL            = 2
+};
+
+//! segments the image using GrabCut algorithm
+CV_EXPORTS_W void grabCut( InputArray img, InputOutputArray mask, Rect rect,
+                           InputOutputArray bgdModel, InputOutputArray fgdModel,
+                           int iterCount, int mode = GC_EVAL );
+
+enum
+{
+    DIST_LABEL_CCOMP = 0,
+    DIST_LABEL_PIXEL = 1
+};
+
+//! builds the discrete Voronoi diagram
+CV_EXPORTS_AS(distanceTransformWithLabels) void distanceTransform( InputArray src, OutputArray dst,
+                                     OutputArray labels, int distanceType, int maskSize,
+                                     int labelType=DIST_LABEL_CCOMP );
+
+//! computes the distance transform map
+CV_EXPORTS_W void distanceTransform( InputArray src, OutputArray dst,
+                                     int distanceType, int maskSize );
+
+enum { FLOODFILL_FIXED_RANGE = 1 << 16, FLOODFILL_MASK_ONLY = 1 << 17 };
+
+//! fills the semi-uniform image region starting from the specified seed point
+CV_EXPORTS int floodFill( InputOutputArray 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 and/or the mask starting from the specified seed point
+CV_EXPORTS_W int floodFill( InputOutputArray image, InputOutputArray mask,
+                            Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0,
+                            Scalar loDiff=Scalar(), Scalar upDiff=Scalar(),
+                            int flags=4 );
+
+
+enum
+{
+    COLOR_BGR2BGRA    =0,
+    COLOR_RGB2RGBA    =COLOR_BGR2BGRA,
+
+    COLOR_BGRA2BGR    =1,
+    COLOR_RGBA2RGB    =COLOR_BGRA2BGR,
+
+    COLOR_BGR2RGBA    =2,
+    COLOR_RGB2BGRA    =COLOR_BGR2RGBA,
+
+    COLOR_RGBA2BGR    =3,
+    COLOR_BGRA2RGB    =COLOR_RGBA2BGR,
+
+    COLOR_BGR2RGB     =4,
+    COLOR_RGB2BGR     =COLOR_BGR2RGB,
+
+    COLOR_BGRA2RGBA   =5,
+    COLOR_RGBA2BGRA   =COLOR_BGRA2RGBA,
+
+    COLOR_BGR2GRAY    =6,
+    COLOR_RGB2GRAY    =7,
+    COLOR_GRAY2BGR    =8,
+    COLOR_GRAY2RGB    =COLOR_GRAY2BGR,
+    COLOR_GRAY2BGRA   =9,
+    COLOR_GRAY2RGBA   =COLOR_GRAY2BGRA,
+    COLOR_BGRA2GRAY   =10,
+    COLOR_RGBA2GRAY   =11,
+
+    COLOR_BGR2BGR565  =12,
+    COLOR_RGB2BGR565  =13,
+    COLOR_BGR5652BGR  =14,
+    COLOR_BGR5652RGB  =15,
+    COLOR_BGRA2BGR565 =16,
+    COLOR_RGBA2BGR565 =17,
+    COLOR_BGR5652BGRA =18,
+    COLOR_BGR5652RGBA =19,
+
+    COLOR_GRAY2BGR565 =20,
+    COLOR_BGR5652GRAY =21,
+
+    COLOR_BGR2BGR555  =22,
+    COLOR_RGB2BGR555  =23,
+    COLOR_BGR5552BGR  =24,
+    COLOR_BGR5552RGB  =25,
+    COLOR_BGRA2BGR555 =26,
+    COLOR_RGBA2BGR555 =27,
+    COLOR_BGR5552BGRA =28,
+    COLOR_BGR5552RGBA =29,
+
+    COLOR_GRAY2BGR555 =30,
+    COLOR_BGR5552GRAY =31,
+
+    COLOR_BGR2XYZ     =32,
+    COLOR_RGB2XYZ     =33,
+    COLOR_XYZ2BGR     =34,
+    COLOR_XYZ2RGB     =35,
+
+    COLOR_BGR2YCrCb   =36,
+    COLOR_RGB2YCrCb   =37,
+    COLOR_YCrCb2BGR   =38,
+    COLOR_YCrCb2RGB   =39,
+
+    COLOR_BGR2HSV     =40,
+    COLOR_RGB2HSV     =41,
+
+    COLOR_BGR2Lab     =44,
+    COLOR_RGB2Lab     =45,
+
+    COLOR_BayerBG2BGR =46,
+    COLOR_BayerGB2BGR =47,
+    COLOR_BayerRG2BGR =48,
+    COLOR_BayerGR2BGR =49,
+
+    COLOR_BayerBG2RGB =COLOR_BayerRG2BGR,
+    COLOR_BayerGB2RGB =COLOR_BayerGR2BGR,
+    COLOR_BayerRG2RGB =COLOR_BayerBG2BGR,
+    COLOR_BayerGR2RGB =COLOR_BayerGB2BGR,
+
+    COLOR_BGR2Luv     =50,
+    COLOR_RGB2Luv     =51,
+    COLOR_BGR2HLS     =52,
+    COLOR_RGB2HLS     =53,
+
+    COLOR_HSV2BGR     =54,
+    COLOR_HSV2RGB     =55,
+
+    COLOR_Lab2BGR     =56,
+    COLOR_Lab2RGB     =57,
+    COLOR_Luv2BGR     =58,
+    COLOR_Luv2RGB     =59,
+    COLOR_HLS2BGR     =60,
+    COLOR_HLS2RGB     =61,
+
+    COLOR_BayerBG2BGR_VNG =62,
+    COLOR_BayerGB2BGR_VNG =63,
+    COLOR_BayerRG2BGR_VNG =64,
+    COLOR_BayerGR2BGR_VNG =65,
+
+    COLOR_BayerBG2RGB_VNG =COLOR_BayerRG2BGR_VNG,
+    COLOR_BayerGB2RGB_VNG =COLOR_BayerGR2BGR_VNG,
+    COLOR_BayerRG2RGB_VNG =COLOR_BayerBG2BGR_VNG,
+    COLOR_BayerGR2RGB_VNG =COLOR_BayerGB2BGR_VNG,
+
+    COLOR_BGR2HSV_FULL = 66,
+    COLOR_RGB2HSV_FULL = 67,
+    COLOR_BGR2HLS_FULL = 68,
+    COLOR_RGB2HLS_FULL = 69,
+
+    COLOR_HSV2BGR_FULL = 70,
+    COLOR_HSV2RGB_FULL = 71,
+    COLOR_HLS2BGR_FULL = 72,
+    COLOR_HLS2RGB_FULL = 73,
+
+    COLOR_LBGR2Lab     = 74,
+    COLOR_LRGB2Lab     = 75,
+    COLOR_LBGR2Luv     = 76,
+    COLOR_LRGB2Luv     = 77,
+
+    COLOR_Lab2LBGR     = 78,
+    COLOR_Lab2LRGB     = 79,
+    COLOR_Luv2LBGR     = 80,
+    COLOR_Luv2LRGB     = 81,
+
+    COLOR_BGR2YUV      = 82,
+    COLOR_RGB2YUV      = 83,
+    COLOR_YUV2BGR      = 84,
+    COLOR_YUV2RGB      = 85,
+
+    COLOR_BayerBG2GRAY = 86,
+    COLOR_BayerGB2GRAY = 87,
+    COLOR_BayerRG2GRAY = 88,
+    COLOR_BayerGR2GRAY = 89,
+
+    //YUV 4:2:0 formats family
+    COLOR_YUV2RGB_NV12 = 90,
+    COLOR_YUV2BGR_NV12 = 91,
+    COLOR_YUV2RGB_NV21 = 92,
+    COLOR_YUV2BGR_NV21 = 93,
+    COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21,
+    COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21,
+
+    COLOR_YUV2RGBA_NV12 = 94,
+    COLOR_YUV2BGRA_NV12 = 95,
+    COLOR_YUV2RGBA_NV21 = 96,
+    COLOR_YUV2BGRA_NV21 = 97,
+    COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21,
+    COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21,
+
+    COLOR_YUV2RGB_YV12 = 98,
+    COLOR_YUV2BGR_YV12 = 99,
+    COLOR_YUV2RGB_IYUV = 100,
+    COLOR_YUV2BGR_IYUV = 101,
+    COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV,
+    COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV,
+    COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12,
+    COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12,
+
+    COLOR_YUV2RGBA_YV12 = 102,
+    COLOR_YUV2BGRA_YV12 = 103,
+    COLOR_YUV2RGBA_IYUV = 104,
+    COLOR_YUV2BGRA_IYUV = 105,
+    COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV,
+    COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV,
+    COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12,
+    COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12,
+
+    COLOR_YUV2GRAY_420 = 106,
+    COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420,
+    COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420,
+    COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420,
+    COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420,
+    COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420,
+    COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420,
+    COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420,
+
+    //YUV 4:2:2 formats family
+    COLOR_YUV2RGB_UYVY = 107,
+    COLOR_YUV2BGR_UYVY = 108,
+    //COLOR_YUV2RGB_VYUY = 109,
+    //COLOR_YUV2BGR_VYUY = 110,
+    COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY,
+    COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY,
+    COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY,
+    COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY,
+
+    COLOR_YUV2RGBA_UYVY = 111,
+    COLOR_YUV2BGRA_UYVY = 112,
+    //COLOR_YUV2RGBA_VYUY = 113,
+    //COLOR_YUV2BGRA_VYUY = 114,
+    COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY,
+    COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY,
+    COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY,
+    COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY,
+
+    COLOR_YUV2RGB_YUY2 = 115,
+    COLOR_YUV2BGR_YUY2 = 116,
+    COLOR_YUV2RGB_YVYU = 117,
+    COLOR_YUV2BGR_YVYU = 118,
+    COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2,
+    COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2,
+    COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2,
+    COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2,
+
+    COLOR_YUV2RGBA_YUY2 = 119,
+    COLOR_YUV2BGRA_YUY2 = 120,
+    COLOR_YUV2RGBA_YVYU = 121,
+    COLOR_YUV2BGRA_YVYU = 122,
+    COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2,
+    COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2,
+    COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2,
+    COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2,
+
+    COLOR_YUV2GRAY_UYVY = 123,
+    COLOR_YUV2GRAY_YUY2 = 124,
+    //COLOR_YUV2GRAY_VYUY = COLOR_YUV2GRAY_UYVY,
+    COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
+    COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
+    COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
+    COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2,
+    COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2,
+
+    // alpha premultiplication
+    COLOR_RGBA2mRGBA = 125,
+    COLOR_mRGBA2RGBA = 126,
+
+    COLOR_RGB2YUV_I420 = 127,
+    COLOR_BGR2YUV_I420 = 128,
+    COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420,
+    COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420,
+
+    COLOR_RGBA2YUV_I420 = 129,
+    COLOR_BGRA2YUV_I420 = 130,
+    COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420,
+    COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420,
+    COLOR_RGB2YUV_YV12  = 131,
+    COLOR_BGR2YUV_YV12  = 132,
+    COLOR_RGBA2YUV_YV12 = 133,
+    COLOR_BGRA2YUV_YV12 = 134,
+
+    COLOR_COLORCVT_MAX  = 135
+};
+
+
+//! converts image from one color space to another
+CV_EXPORTS_W void cvtColor( InputArray src, OutputArray dst, int code, int dstCn=0 );
+
+//! raster image moments
+class CV_EXPORTS_W_MAP Moments
+{
+public:
+    //! the default constructor
+    Moments();
+    //! the full constructor
+    Moments(double m00, double m10, double m01, double m20, double m11,
+            double m02, double m30, double m21, double m12, double m03 );
+    //! the conversion from CvMoments
+    Moments( const CvMoments& moments );
+    //! the conversion to CvMoments
+    operator CvMoments() const;
+
+    //! spatial moments
+    CV_PROP_RW double  m00, m10, m01, m20, m11, m02, m30, m21, m12, m03;
+    //! central moments
+    CV_PROP_RW double  mu20, mu11, mu02, mu30, mu21, mu12, mu03;
+    //! central normalized moments
+    CV_PROP_RW double  nu20, nu11, nu02, nu30, nu21, nu12, nu03;
+};
+
+//! computes moments of the rasterized shape or a vector of points
+CV_EXPORTS_W Moments moments( InputArray array, bool binaryImage=false );
+
+//! computes 7 Hu invariants from the moments
+CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] );
+CV_EXPORTS_W void HuMoments( const Moments& m, CV_OUT OutputArray hu );
+
+//! type of the template matching operation
+enum { TM_SQDIFF=0, TM_SQDIFF_NORMED=1, TM_CCORR=2, TM_CCORR_NORMED=3, TM_CCOEFF=4, TM_CCOEFF_NORMED=5 };
+
+//! computes the proximity map for the raster template and the image where the template is searched for
+CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ,
+                                 OutputArray result, int method );
+
+//! mode of the contour retrieval algorithm
+enum
+{
+    RETR_EXTERNAL=CV_RETR_EXTERNAL, //!< retrieve only the most external (top-level) contours
+    RETR_LIST=CV_RETR_LIST, //!< retrieve all the contours without any hierarchical information
+    RETR_CCOMP=CV_RETR_CCOMP, //!< retrieve the connected components (that can possibly be nested)
+    RETR_TREE=CV_RETR_TREE, //!< retrieve all the contours and the whole hierarchy
+    RETR_FLOODFILL=CV_RETR_FLOODFILL
+};
+
+//! the contour approximation algorithm
+enum
+{
+    CHAIN_APPROX_NONE=CV_CHAIN_APPROX_NONE,
+    CHAIN_APPROX_SIMPLE=CV_CHAIN_APPROX_SIMPLE,
+    CHAIN_APPROX_TC89_L1=CV_CHAIN_APPROX_TC89_L1,
+    CHAIN_APPROX_TC89_KCOS=CV_CHAIN_APPROX_TC89_KCOS
+};
+
+//! retrieves contours and the hierarchical information from black-n-white image.
+CV_EXPORTS_W void findContours( InputOutputArray image, OutputArrayOfArrays contours,
+                              OutputArray hierarchy, int mode,
+                              int method, Point offset=Point());
+
+//! retrieves contours from black-n-white image.
+CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contours,
+                              int mode, int method, Point offset=Point());
+
+//! draws contours in the image
+CV_EXPORTS_W void drawContours( InputOutputArray image, InputArrayOfArrays contours,
+                              int contourIdx, const Scalar& color,
+                              int thickness=1, int lineType=8,
+                              InputArray hierarchy=noArray(),
+                              int maxLevel=INT_MAX, Point offset=Point() );
+
+//! approximates contour or a curve using Douglas-Peucker algorithm
+CV_EXPORTS_W void approxPolyDP( InputArray curve,
+                                OutputArray approxCurve,
+                                double epsilon, bool closed );
+
+//! computes the contour perimeter (closed=true) or a curve length
+CV_EXPORTS_W double arcLength( InputArray curve, bool closed );
+//! computes the bounding rectangle for a contour
+CV_EXPORTS_W Rect boundingRect( InputArray points );
+//! computes the contour area
+CV_EXPORTS_W double contourArea( InputArray contour, bool oriented=false );
+//! computes the minimal rotated rectangle for a set of points
+CV_EXPORTS_W RotatedRect minAreaRect( InputArray points );
+//! computes the minimal enclosing circle for a set of points
+CV_EXPORTS_W void minEnclosingCircle( InputArray points,
+                                      CV_OUT Point2f& center, CV_OUT float& radius );
+//! matches two contours using one of the available algorithms
+CV_EXPORTS_W double matchShapes( InputArray contour1, InputArray contour2,
+                                 int method, double parameter );
+//! computes convex hull for a set of 2D points.
+CV_EXPORTS_W void convexHull( InputArray points, OutputArray hull,
+                              bool clockwise=false, bool returnPoints=true );
+//! computes the contour convexity defects
+CV_EXPORTS_W void convexityDefects( InputArray contour, InputArray convexhull, OutputArray convexityDefects );
+
+//! returns true if the contour is convex. Does not support contours with self-intersection
+CV_EXPORTS_W bool isContourConvex( InputArray contour );
+
+//! finds intersection of two convex polygons
+CV_EXPORTS_W float intersectConvexConvex( InputArray _p1, InputArray _p2,
+                                          OutputArray _p12, bool handleNested=true );
+
+//! fits ellipse to the set of 2D points
+CV_EXPORTS_W RotatedRect fitEllipse( InputArray points );
+
+//! fits line to the set of 2D points using M-estimator algorithm
+CV_EXPORTS_W void fitLine( InputArray points, OutputArray line, int distType,
+                           double param, double reps, double aeps );
+//! checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary
+CV_EXPORTS_W double pointPolygonTest( InputArray contour, Point2f pt, bool measureDist );
+
+
+class CV_EXPORTS_W Subdiv2D
+{
+public:
+    enum
+    {
+        PTLOC_ERROR = -2,
+        PTLOC_OUTSIDE_RECT = -1,
+        PTLOC_INSIDE = 0,
+        PTLOC_VERTEX = 1,
+        PTLOC_ON_EDGE = 2
+    };
+
+    enum
+    {
+        NEXT_AROUND_ORG   = 0x00,
+        NEXT_AROUND_DST   = 0x22,
+        PREV_AROUND_ORG   = 0x11,
+        PREV_AROUND_DST   = 0x33,
+        NEXT_AROUND_LEFT  = 0x13,
+        NEXT_AROUND_RIGHT = 0x31,
+        PREV_AROUND_LEFT  = 0x20,
+        PREV_AROUND_RIGHT = 0x02
+    };
+
+    CV_WRAP Subdiv2D();
+    CV_WRAP Subdiv2D(Rect rect);
+    CV_WRAP void initDelaunay(Rect rect);
+
+    CV_WRAP int insert(Point2f pt);
+    CV_WRAP void insert(const vector<Point2f>& ptvec);
+    CV_WRAP int locate(Point2f pt, CV_OUT int& edge, CV_OUT int& vertex);
+
+    CV_WRAP int findNearest(Point2f pt, CV_OUT Point2f* nearestPt=0);
+    CV_WRAP void getEdgeList(CV_OUT vector<Vec4f>& edgeList) const;
+    CV_WRAP void getTriangleList(CV_OUT vector<Vec6f>& triangleList) const;
+    CV_WRAP void getVoronoiFacetList(const vector<int>& idx, CV_OUT vector<vector<Point2f> >& facetList,
+                                     CV_OUT vector<Point2f>& facetCenters);
+
+    CV_WRAP Point2f getVertex(int vertex, CV_OUT int* firstEdge=0) const;
+
+    CV_WRAP int getEdge( int edge, int nextEdgeType ) const;
+    CV_WRAP int nextEdge(int edge) const;
+    CV_WRAP int rotateEdge(int edge, int rotate) const;
+    CV_WRAP int symEdge(int edge) const;
+    CV_WRAP int edgeOrg(int edge, CV_OUT Point2f* orgpt=0) const;
+    CV_WRAP int edgeDst(int edge, CV_OUT Point2f* dstpt=0) const;
+
+protected:
+    int newEdge();
+    void deleteEdge(int edge);
+    int newPoint(Point2f pt, bool isvirtual, int firstEdge=0);
+    void deletePoint(int vtx);
+    void setEdgePoints( int edge, int orgPt, int dstPt );
+    void splice( int edgeA, int edgeB );
+    int connectEdges( int edgeA, int edgeB );
+    void swapEdges( int edge );
+    int isRightOf(Point2f pt, int edge) const;
+    void calcVoronoi();
+    void clearVoronoi();
+    void checkSubdiv() const;
+
+    struct CV_EXPORTS Vertex
+    {
+        Vertex();
+        Vertex(Point2f pt, bool _isvirtual, int _firstEdge=0);
+        bool isvirtual() const;
+        bool isfree() const;
+        int firstEdge;
+        int type;
+        Point2f pt;
+    };
+    struct CV_EXPORTS QuadEdge
+    {
+        QuadEdge();
+        QuadEdge(int edgeidx);
+        bool isfree() const;
+        int next[4];
+        int pt[4];
+    };
+
+    vector<Vertex> vtx;
+    vector<QuadEdge> qedges;
+    int freeQEdge;
+    int freePoint;
+    bool validGeometry;
+
+    int recentEdge;
+    Point2f topLeft;
+    Point2f bottomRight;
+};
+
+}
+
+#endif /* __cplusplus */
+
+#endif
+
+/* End of file. */