Implementation of PCT signature extractor (position-color-texture) and…

Implementation of PCT signature extractor (position-color-texture) and evaluation of their Signature Quadratic Form Distance (SQFD).

modules/xfeatures2d/doc/xfeatures2d.bib

@@ -92,3 +92,22 @@
   booktitle = "Computer Vision and Pattern Recognition",
   year = {2013}
 }
+
+@article{KrulisLS16,
+  author    = {Martin Krulis and Jakub Lokoc and Tomas Skopal},
+  title     = {Efficient extraction of clustering-based feature signatures using {GPU} architectures},
+  journal   = {Multimedia Tools Appl.},
+  volume    = {75},
+  number    = {13},
+  pages     = {8071--8103},
+  year      = {2016}
+}
+
+@inproceedings{BeecksUS10,
+  author    = {Christian Beecks and Merih Seran Uysal and Thomas Seidl},
+  title     = {Signature Quadratic Form Distance},
+  booktitle = {{CIVR}},
+  pages     = {438--445},
+  publisher = {{ACM}},
+  year      = {2010}
+}

modules/xfeatures2d/samples/pct_signatures.cpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+#include <opencv2/core.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/xfeatures2d.hpp>
+
+#include <iostream>
+#include <string>
+
+using namespace std;
+using namespace cv;
+using namespace xfeatures2d;
+
+
+void printHelpMessage(void);
+void printHelpMessage(void)
+{
+    cout << "Example of the PCTSignatures algorithm computing and visualizing\n"
+        "image signature for one image, or comparing multiple images with the first\n"
+        "image using the signature quadratic form distance.\n\n"
+        "Usage: pct_signatures ImageToProcessAndDisplay\n"
+        "or:    pct_signatures ReferenceImage [ImagesToCompareWithTheReferenceImage]\n\n"
+        "The program has 2 modes:\n"
+        "- single argument: program computes and visualizes the image signature\n"
+        "- multiple arguments: program compares the first image to the others\n"
+        "  using pct signatures and signature quadratic form distance (SQFD)";
+}
+
+/** @brief
+
+Example of the PCTSignatures algorithm.
+
+The program has 2 modes:
+- single argument mode, where the program computes and visualizes the image signature
+- multiple argument mode, where the program compares the first image to the others
+using signatures and signature quadratic form distance (SQFD)
+
+*/
+int main(int argc, char** argv)
+{
+    if (argc < 2)                               // Check arguments
+    {
+        printHelpMessage();
+        return 1;
+    }
+
+    Mat source;
+    source = imread(argv[1]);                   // Read the file
+
+    if (!source.data)                           // Check for invalid input
+    {
+        cerr << "Could not open or find the image: " << argv[1];
+        return -1;
+    }
+
+    Mat signature, result;                      // define variables
+    int initSampleCount = 2000;
+    int initSeedCount = 400;
+    int grayscaleBitsPerPixel = 4;
+    vector<Point2f> initPoints;
+
+    namedWindow("Source", WINDOW_AUTOSIZE);     // Create windows for display.
+    namedWindow("Result", WINDOW_AUTOSIZE);
+
+                                                // create the algorithm
+    PCTSignatures::generateInitPoints(initPoints, initSampleCount, PCTSignatures::UNIFORM);
+    Ptr<PCTSignatures> pctSignatures = PCTSignatures::create(initPoints, initSeedCount);
+    pctSignatures->setGrayscaleBits(grayscaleBitsPerPixel);
+
+                                                // compute and visualize the first image
+    double start = (double)getTickCount();
+    pctSignatures->computeSignature(source, signature);
+    double end = (double)getTickCount();
+    cout << "Signature of the reference image computed in " << (end - start) / (getTickFrequency() * 1.0f) << " seconds." << endl;
+    PCTSignatures::drawSignature(source, signature, result);
+
+    imshow("Source", source);                   // show the result
+    imshow("Result", result);
+
+    if (argc == 2)          // single image -> finish right after the visualization
+    {
+        waitKey(0);         // Wait for user input
+        return 0;
+    }
+    // multiple images -> compare to the first one
+    else
+    {
+        vector<Mat> images;
+        vector<Mat> signatures;
+        vector<float> distances;
+
+        for (int i = 2; i < argc; i++)
+        {
+            Mat image = imread(argv[i]);
+            if (!source.data)                               // Check for invalid input
+            {
+                cerr << "Could not open or find the image: " << argv[i] << std::endl;
+                return 1;
+            }
+            images.push_back(image);
+        }
+
+        pctSignatures->computeSignatures(images, signatures);
+        Ptr<PCTSignaturesSQFD> pctSQFD = PCTSignaturesSQFD::create();
+        pctSQFD->computeQuadraticFormDistances(signature, signatures, distances);
+
+        for (int i = 0; i < (int)(distances.size()); i++)
+        {
+            cout << "Image: " << argv[i + 2] << ", similarity: " << distances[i] << endl;
+        }
+        waitKey(0); // Wait for user input
+    }
+
+    return 0;
+}

modules/xfeatures2d/samples/pct_webcam.cpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+#include <opencv2/core.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/xfeatures2d.hpp>
+
+#include <iostream>
+#include <string>
+
+using namespace std;
+using namespace cv;
+using namespace xfeatures2d;
+
+
+void printHelpMessage(void);
+void printHelpMessage(void)
+{
+    cout << "Example of the PCTSignatures algorithm.\n\n"
+        "This program computes and visualizes position-color-texture signatures\n"
+        "using images from webcam if available.\n\n"
+        "Usage:\n"
+        "pct_webcam [sample_count] [seed_count]\n"
+        "Note: sample_count must be greater or equal to seed_count.";
+}
+
+
+/** @brief
+
+Example of the PCTSignatures algorithm.
+
+This program computes and visualizes position-color-texture signatures
+of images taken from webcam if available.
+*/
+int main(int argc, char** argv)
+{
+    // define variables
+    Mat frame, signature, result;
+    int initSampleCount = 2000;
+    int initSeedCount = 400;
+    int grayscaleBitsPerPixel = 4;
+
+    // parse for help argument
+    {
+        for (int i = 1; i < argc; i++)
+        {
+            if ((string)argv[i] == "-h" || (string)argv[i] == "--help")
+            {
+                printHelpMessage();
+                return 0;
+            }
+        }
+    }
+
+    // parse optional arguments
+    if (argc > 1)               // sample count
+    {
+        initSampleCount = atoi(argv[1]);
+        if (initSampleCount <= 0)
+        {
+            cerr << "Sample count have to be a positive integer: " << argv[1] << endl;
+            return 1;
+        }
+        initSeedCount = (int)floor(initSampleCount / 4);
+        initSeedCount = std::max(1, initSeedCount);     // fallback if sample count == 1
+    }
+    if (argc > 2)               // seed count
+    {
+        initSeedCount = atoi(argv[2]);
+        if (initSeedCount <= 0)
+        {
+            cerr << "Seed count have to be a positive integer: " << argv[2] << endl;
+            return 1;
+        }
+        if (initSeedCount > initSampleCount)
+        {
+            cerr << "Seed count have to be lower or equal to sample count!" << endl;
+            return 1;
+        }
+    }
+
+    // create algorithm
+    Ptr<PCTSignatures> pctSignatures = PCTSignatures::create(initSampleCount, initSeedCount, PCTSignatures::UNIFORM);
+    pctSignatures->setGrayscaleBits(grayscaleBitsPerPixel);
+
+    // open video capture device
+    VideoCapture videoCapture;
+    if (!videoCapture.open(0))
+    {
+        cerr << "Unable to open the first video capture device with ID = 0!" << endl;
+        return 1;
+    }
+
+    // Create windows for display.
+    namedWindow("Source", WINDOW_AUTOSIZE);
+    namedWindow("Result", WINDOW_AUTOSIZE);
+
+    // run drawing loop
+    for (;;)
+    {
+        videoCapture >> frame;
+        if (frame.empty()) break; // end of video stream
+
+        pctSignatures->computeSignature(frame, signature);
+        PCTSignatures::drawSignature(Mat::zeros(frame.size(), frame.type()), signature, result);
+
+        imshow("Source", frame);                // Show our images inside the windows.
+        imshow("Result", result);
+
+        if (waitKey(1) == 27) break;            // stop videocapturing by pressing ESC
+    }
+
+    return 0;
+}

modules/xfeatures2d/src/pct_signatures/constants.hpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+
+#ifndef _OPENCV_XFEATURES_2D_PCT_SIGNATURES_CONSTANTS_HPP_
+#define _OPENCV_XFEATURES_2D_PCT_SIGNATURES_CONSTANTS_HPP_
+
+#ifdef __cplusplus
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+            const int SIGNATURE_DIMENSION = 8;
+
+            const int WEIGHT_IDX = 0;
+            const int X_IDX = 1;
+            const int Y_IDX = 2;
+            const int L_IDX = 3;
+            const int A_IDX = 4;
+            const int B_IDX = 5;
+            const int CONTRAST_IDX = 6;
+            const int ENTROPY_IDX = 7;
+
+            const float L_COLOR_RANGE = 100;
+            const float A_COLOR_RANGE = 127;
+            const float B_COLOR_RANGE = 127;
+
+            const float SAMPLER_CONTRAST_NORMALIZER = 25.0;   // both determined empirically
+            const float SAMPLER_ENTROPY_NORMALIZER = 4.0;
+
+        }
+    }
+}
+
+#endif
+
+#endif

modules/xfeatures2d/src/pct_signatures/distance.hpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+
+#ifndef _OPENCV_XFEATURES_2D_PCT_SIGNATURES_DISTANCE_HPP_
+#define _OPENCV_XFEATURES_2D_PCT_SIGNATURES_DISTANCE_HPP_
+
+#ifdef __cplusplus
+#include "precomp.hpp"
+
+#include "constants.hpp"
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+
+            static inline float distanceL0_25(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    result += std::sqrt(std::sqrt(std::abs(difference)));
+                }
+                result *= result;
+                return result * result;
+            }
+
+
+            static inline float distanceL0_5(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    result += std::sqrt(std::abs(difference));
+                }
+                return result * result;
+            }
+
+
+            static inline float distanceL1(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    result += std::abs(difference);
+                }
+                return result;
+            }
+
+
+            static inline float distanceL2(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    result += difference * difference;
+                }
+                return (float)std::sqrt(result);
+            }
+
+
+            static inline float distanceL2Squared(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    result += difference * difference;
+                }
+                return result;
+            }
+
+
+            static inline float distanceL5(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    result += std::abs(difference) * difference * difference * difference * difference;
+                }
+                return std::pow(result, (float)0.2);
+            }
+
+
+            static inline float distanceLInfinity(
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float result = (float)0.0;
+                for (int d = 1; d < SIGNATURE_DIMENSION; ++d)
+                {
+                    float difference = points1.at<float>(idx1, d) - points2.at<float>(idx2, d);
+                    if (difference > result)
+                    {
+                        result = difference;
+                    }
+                }
+                return result;
+            }
+
+
+            /**
+            * @brief Computed distance between two centroids using given distance function.
+            * @param distanceFunction Distance function selector.
+            * @param points1 The first signature matrix - one centroid in each row.
+            * @param idx1 ID of centroid in the first signature
+            * @param points2 The second signature matrix - one centroid in each row.
+            * @param idx2 ID of centroid in the first signature
+            * @note The first column of a signature contains weights,
+            *       so only rows 1 to SIGNATURE_DIMENSION are used.
+            */
+            static inline float computeDistance(
+                const int distanceFunction,
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                switch (distanceFunction)
+                {
+                case PCTSignatures::L0_25:
+                    return distanceL0_25(points1, idx1, points2, idx2);
+                case PCTSignatures::L0_5:
+                    return distanceL0_5(points1, idx1, points2, idx2);
+                case PCTSignatures::L1:
+                    return distanceL1(points1, idx1, points2, idx2);
+                case PCTSignatures::L2:
+                    return distanceL2(points1, idx1, points2, idx2);
+                case PCTSignatures::L2SQUARED:
+                    return distanceL2Squared(points1, idx1, points2, idx2);
+                case PCTSignatures::L5:
+                    return distanceL5(points1, idx1, points2, idx2);
+                case PCTSignatures::L_INFINITY:
+                    return distanceLInfinity(points1, idx1, points2, idx2);
+                default:
+                    CV_Error(Error::StsBadArg, "Distance function not implemented!");
+                    return -1;
+                }
+            }
+        }
+    }
+}
+
+
+#endif
+
+#endif

modules/xfeatures2d/src/pct_signatures/grayscale_bitmap.cpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 80718103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+#include "precomp.hpp"
+
+#include "grayscale_bitmap.hpp"
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+            GrayscaleBitmap::GrayscaleBitmap(InputArray _bitmap, int bitsPerPixel)
+                : mBitsPerPixel(bitsPerPixel)
+            {
+                Mat bitmap = _bitmap.getMat();
+                if (bitmap.empty())
+                {
+                    CV_Error(Error::StsBadArg, "Input bitmap is empty");
+                }
+                if (bitmap.depth() != CV_8U && bitmap.depth() != CV_16U)
+                {
+                    CV_Error(Error::StsUnsupportedFormat, "Input bitmap depth must be CV_8U or CV_16U");
+                }
+                if (bitmap.depth() == CV_8U)
+                {
+                    bitmap.convertTo(bitmap, CV_16U, 257);
+                }
+
+                Mat grayscaleBitmap;
+                cvtColor(bitmap, grayscaleBitmap, COLOR_BGR2GRAY);
+
+                mWidth = bitmap.cols;
+                mHeight = bitmap.rows;
+
+                if (bitsPerPixel <= 0 || bitsPerPixel > 8)
+                {
+                    CV_Error_(Error::StsBadArg, ("Invalid number of bits per pixel %d. Only values in range [1..8] are accepted.", bitsPerPixel));
+                }
+
+                // Allocate space for pixel data.
+                int pixelsPerItem = 32 / mBitsPerPixel;
+                mData.resize((mWidth*mHeight + pixelsPerItem - 1) / pixelsPerItem);
+
+                // Convert the bitmap to grayscale and fill the pixel data.
+                CV_Assert(grayscaleBitmap.depth() == CV_16U);
+                for (int y = 0; y < mHeight; y++)
+                {
+                    for (int x = 0; x < mWidth; x++)
+                    {
+                        uint grayVal = ((uint)grayscaleBitmap.at<ushort>((int)y, (int)x)) >> (16 - mBitsPerPixel);
+                        setPixel(x, y, grayVal);
+                    }
+                }
+                // Prepare the preallocated contrast matrix for contrast-entropy computations
+                mCoOccurrenceMatrix.resize(1 << (mBitsPerPixel * 2));   // mCoOccurrenceMatrix size = maxPixelValue^2
+            }
+
+
+            // HOT PATH 30%
+            void GrayscaleBitmap::getContrastEntropy(int x, int y, float& contrast, float& entropy, int radius)
+            {
+                int fromX = (x > radius) ? x - radius : 0;
+                int fromY = (y > radius) ? y - radius : 0;
+                int toX = std::min<int>(mWidth - 1, x + radius + 1);
+                int toY = std::min<int>(mHeight - 1, y + radius + 1);
+                for (int j = fromY; j < toY; ++j)
+                {
+                    for (int i = fromX; i < toX; ++i)                               // for each pixel in the window
+                    {
+                        updateCoOccurrenceMatrix(getPixel(i, j), getPixel(i, j + 1));        // match every pixel with all 8 its neighbours
+                        updateCoOccurrenceMatrix(getPixel(i, j), getPixel(i + 1, j));
+                        updateCoOccurrenceMatrix(getPixel(i, j), getPixel(i + 1, j + 1));
+                        updateCoOccurrenceMatrix(getPixel(i + 1, j), getPixel(i, j + 1));    // 4 updates per pixel in the window
+                    }
+                }
+
+                contrast = 0.0;
+                entropy = 0.0;
+
+                uint pixelsScale = 1 << mBitsPerPixel;
+                float normalizer = (float)((toX - fromX) * (toY - fromY) * 4);            // four increments per pixel in the window (see above)
+                for (int j = 0; j < (int)pixelsScale; ++j)                              // iterate row in a 2D histogram
+                {
+                    for (int i = 0; i <= j; ++i)                                        // iterate column up to the diagonal in 2D histogram
+                    {
+                        if (mCoOccurrenceMatrix[j*pixelsScale + i] != 0)                // consider only non-zero values
+                        {
+                            float value = (float)mCoOccurrenceMatrix[j*pixelsScale + i] / normalizer; // normalize value by number of histogram updates
+                            contrast += (i - j) * (i - j) * value;          // compute contrast
+                            entropy -= value * std::log(value);             // compute entropy
+                            mCoOccurrenceMatrix[j*pixelsScale + i] = 0;     // clear the histogram array for the next computation
+                        }
+                    }
+                }
+            }
+
+
+            void GrayscaleBitmap::convertToMat(OutputArray _bitmap, bool normalize) const
+            {
+                _bitmap.create((int)getHeight(), (int)getWidth(), CV_8U);
+                Mat bitmap = _bitmap.getMat();
+
+                for (int y = 0; y < getHeight(); ++y)
+                {
+                    for (int x = 0; x < getWidth(); ++x)
+                    {
+                        uint pixel = getPixel(x, y);
+                        if (normalize && mBitsPerPixel < 8)
+                        {
+                            pixel <<= 8 - mBitsPerPixel;
+                        }
+                        else if (normalize && mBitsPerPixel > 8)
+                        {
+                            pixel >>= mBitsPerPixel - 8;
+                        }
+                        bitmap.at<uchar>((int)y, (int)x) = (uchar)pixel;
+                    }
+                }
+            }
+
+        }
+    }
+}

modules/xfeatures2d/src/pct_signatures/grayscale_bitmap.hpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+
+#ifndef _OPENCV_XFEATURES_2D_PCT_SIGNATURES_GRAYSCALE_BITMAP_HPP_
+#define _OPENCV_XFEATURES_2D_PCT_SIGNATURES_GRAYSCALE_BITMAP_HPP_
+
+#ifdef __cplusplus
+
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+            /**
+            * @brief Specific implementation of grayscale bitmap. This bitmap is used
+            *       to compute contrast and entropy features from surroundings of a pixel.
+            */
+            class GrayscaleBitmap
+            {
+            public:
+                /**
+                * @brief Initialize the grayscale bitmap from regular bitmap.
+                * @param bitmap Bitmap used as source of data.
+                * @param bitsPerPixel How many bits occupy one pixel in grayscale (e.g., 8 ~ 256 grayscale values).
+                *       Must be within [1..8] range.
+                */
+                GrayscaleBitmap(InputArray bitmap, int bitsPerPixel = 4);
+
+                /**
+                * @brief Return the width of the image in pixels.
+                */
+                int getWidth() const
+                {
+                    return mWidth;
+                }
+
+                /**
+                * @brief Return the height of the image in pixels.
+                */
+                int getHeight() const
+                {
+                    return mHeight;
+                }
+
+                /**
+                * @brief Return the height of the image in pixels.
+                */
+                int getBitsPerPixel() const
+                {
+                    return mBitsPerPixel;
+                }
+
+
+                /**
+                * @brief Compute contrast and entropy at selected coordinates.
+                * @param x The horizontal coordinate of the pixel (0..width-1).
+                * @param y The vertical coordinate of the pixel (0..height-1).
+                * @param contrast Output variable where contrast value is saved.
+                * @param entropy Output variable where entropy value is saved.
+                * @param radius Radius of the rectangular window around selected pixel used for computing
+                *       contrast and entropy. Size of the window side is (2*radius + 1).
+                *       The window is cropped if [x,y] is too near the image border.
+                */
+                void getContrastEntropy(
+                    int x,
+                    int y,
+                    float& contrast,
+                    float& entropy,
+                    int windowRadius = 3);
+
+                /**
+                * @brief Converts to OpenCV CV_8U Mat for debug and visualization purposes.
+                * @param bitmap OutputArray proxy where Mat will be written.
+                * @param normalize Whether to normalize the bitmap to the whole range of 255 values
+                *       to improve contrast.
+                */
+                void convertToMat(OutputArray bitmap, bool normalize = true) const;
+
+
+            private:
+                /**
+                * @brief Width of the image.
+                */
+                int mWidth;
+
+                /**
+                * @brief Height of the image.
+                */
+                int mHeight;
+
+                /**
+                * @brief Number of bits per pixel.
+                */
+                int mBitsPerPixel;
+
+                /**
+                * @brief Pixel data packed in 32-bit uints.
+                */
+                std::vector<uint> mData;
+
+                /**
+                * @brief Tmp matrix used for computing contrast and entropy.
+                */
+                std::vector<uint> mCoOccurrenceMatrix;
+
+
+                /**
+                * @brief Get pixel from packed data vector.
+                * @param x The horizontal coordinate of the pixel (0..width-1).
+                * @param y The vertical coordinate of the pixel (0..height-1).
+                * @return Grayscale value (0 ~ black, 2^bitPerPixel - 1 ~ white).
+                */
+                uint inline getPixel(int x, int y) const
+                {
+                    int pixelsPerItem = 32 / mBitsPerPixel;
+                    int offset = y*mWidth + x;
+                    int shift = (offset % pixelsPerItem) * mBitsPerPixel;
+                    uint mask = (1 << mBitsPerPixel) - 1;
+                    return (mData[offset / pixelsPerItem] >> shift) & mask;
+                }
+
+                /**
+                * @brief Set pixel in the packed data vector.
+                * @param x The horizontal coordinate of the pixel (0..width-1).
+                * @param y The vertical coordinate of the pixel (0..height-1).
+                * @param val Grayscale value (0 ~ black, 2^bitPerPixel - 1 ~ white).
+                */
+                void inline setPixel(int x, int y, uint val)
+                {
+                    int pixelsPerItem = 32 / mBitsPerPixel;
+                    int offset = y*mWidth + x;
+                    int shift = (offset % pixelsPerItem) * mBitsPerPixel;
+                    uint mask = (1 << mBitsPerPixel) - 1;
+                    val &= mask;
+                    mData[offset / pixelsPerItem] &= ~(mask << shift);
+                    mData[offset / pixelsPerItem] |= val << shift;
+                }
+
+                /**
+                * @brief Perform an update of contrast matrix.
+                */
+                void inline updateCoOccurrenceMatrix(uint a, uint b)
+                {
+                    // co-occurrence matrix is symmetric
+                    // merge to a variable with greater higher bits
+                    // to accumulate just in upper triangle in co-occurrence matrix for efficiency
+                    int offset = (int)((a > b) ? (a << mBitsPerPixel) + b : a + (b << mBitsPerPixel));
+                    mCoOccurrenceMatrix[offset]++;
+                }
+
+
+            };
+        }
+    }
+}
+
+
+#endif
+
+#endif

modules/xfeatures2d/src/pct_signatures/pct_clusterizer.hpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+
+#ifndef _OPENCV_XFEATURES_2D_PCT_SIGNATURES_CLUSTERIZER_HPP_
+#define _OPENCV_XFEATURES_2D_PCT_SIGNATURES_CLUSTERIZER_HPP_
+
+#ifdef __cplusplus
+
+
+#include "constants.hpp"
+#include "distance.hpp"
+
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+            class PCTClusterizer : public Algorithm
+            {
+            public:
+
+                static Ptr<PCTClusterizer> create(
+                    const std::vector<int>& initSeedIndexes,
+                    int iterations = 10,
+                    int maxClusters = 768,  // max for Fermi GPU architecture
+                    int clusterMinSize = 2,
+                    float joiningDistance = 0.2,
+                    float dropThreshold = 0,
+                    int distanceFunction = PCTSignatures::L2);
+
+
+                /**** Accessors ****/
+
+                virtual int getIterationCount() const = 0;
+                virtual std::vector<int> getInitSeedIndexes() const = 0;
+                virtual int getMaxClustersCount() const = 0;
+                virtual int getClusterMinSize() const = 0;
+                virtual float getJoiningDistance() const = 0;
+                virtual float getDropThreshold() const = 0;
+                virtual int getDistanceFunction() const = 0;
+
+
+                virtual void setIterationCount(int iterationCount) = 0;
+                virtual void setInitSeedIndexes(std::vector<int> initSeedIndexes) = 0;
+                virtual void setMaxClustersCount(int maxClustersCount) = 0;
+                virtual void setClusterMinSize(int clusterMinSize) = 0;
+                virtual void setJoiningDistance(float joiningDistance) = 0;
+                virtual void setDropThreshold(float dropThreshold) = 0;
+                virtual void setDistanceFunction(int distanceFunction) = 0;
+
+                /**
+                * @brief K-means algorithm over the sampled points producing centroids as signatures.
+                * @param samples List of sampled points.
+                * @param signature Output list of computed centroids - the signature of the image.
+                */
+                virtual void clusterize(InputArray samples, OutputArray signature) = 0;
+            };
+        }
+    }
+}
+
+
+#endif
+
+#endif

modules/xfeatures2d/src/pct_signatures/pct_sampler.hpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+
+#ifndef _OPENCV_XFEATURES_2D_PCT_SIGNATURES_SAMPLER_HPP_
+#define _OPENCV_XFEATURES_2D_PCT_SIGNATURES_SAMPLER_HPP_
+
+#ifdef __cplusplus
+
+
+#include "constants.hpp"
+#include "grayscale_bitmap.hpp"
+
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+            class PCTSampler : public Algorithm
+            {
+            public:
+
+                static Ptr<PCTSampler> create(
+                    const std::vector<Point2f>& initSamplingPoints,
+                    int                     grayscaleBits = 4,
+                    int                     windowRadius = 3);
+
+
+                /**
+                * @brief Sampling algorithm that produces samples of the input image
+                *       using the stored sampling point locations.
+                * @param image Input image.
+                * @param signature Output list of computed image samples.
+                */
+                virtual void sample(InputArray image, OutputArray samples) const = 0;
+
+
+                /**** accessors ****/
+
+                virtual int getSampleCount() const = 0;
+                virtual int getGrayscaleBits() const = 0;
+                virtual int getWindowRadius() const = 0;
+                virtual float getWeightX() const = 0;
+                virtual float getWeightY() const = 0;
+                virtual float getWeightL() const = 0;
+                virtual float getWeightA() const = 0;
+                virtual float getWeightB() const = 0;
+                virtual float getWeightConstrast() const = 0;
+                virtual float getWeightEntropy() const = 0;
+
+                virtual std::vector<Point2f> getSamplingPoints() const = 0;
+
+
+                virtual void setGrayscaleBits(int grayscaleBits) = 0;
+                virtual void setWindowRadius(int radius) = 0;
+                virtual void setWeightX(float weight) = 0;
+                virtual void setWeightY(float weight) = 0;
+                virtual void setWeightL(float weight) = 0;
+                virtual void setWeightA(float weight) = 0;
+                virtual void setWeightB(float weight) = 0;
+                virtual void setWeightContrast(float weight) = 0;
+                virtual void setWeightEntropy(float weight) = 0;
+
+                virtual void setWeight(int idx, float value) = 0;
+                virtual void setWeights(const std::vector<float>& weights) = 0;
+                virtual void setTranslation(int idx, float value) = 0;
+                virtual void setTranslations(const std::vector<float>& translations) = 0;
+
+                virtual void setSamplingPoints(std::vector<Point2f> samplingPoints) = 0;
+
+            };
+
+        }
+    }
+}
+
+
+#endif
+
+#endif

modules/xfeatures2d/src/pct_signatures/similarity.hpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+
+#ifndef _OPENCV_XFEATURES_2D_PCT_SIGNATURES_SIMILARITY_HPP_
+#define _OPENCV_XFEATURES_2D_PCT_SIGNATURES_SIMILARITY_HPP_
+
+#ifdef __cplusplus
+
+#include "precomp.hpp"
+
+#include "distance.hpp"
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+
+            static inline float minusSimilarity(
+                const int distancefunction,
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                return -computeDistance(distancefunction, points1, idx1, points2, idx2);
+            }
+
+
+            static inline float gaussianSimilarity(
+                const int distancefunction,
+                const float alpha,
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                float distance = computeDistance(distancefunction, points1, idx1, points2, idx2);
+                return exp(-alpha + distance * distance);
+            }
+
+
+            static inline float heuristicSimilarity(
+                const int distancefunction,
+                const float alpha,
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                return 1 / (alpha + computeDistance(distancefunction, points1, idx1, points2, idx2));
+            }
+
+
+
+            static inline float computeSimilarity(
+                const int distancefunction,
+                const int similarity,
+                const float similarityParameter,
+                const Mat& points1, int idx1,
+                const Mat& points2, int idx2)
+            {
+                switch (similarity)
+                {
+                case PCTSignatures::MINUS:
+                    return minusSimilarity(distancefunction, points1, idx1, points2, idx2);
+                case PCTSignatures::GAUSSIAN:
+                    return gaussianSimilarity(distancefunction, similarityParameter, points1, idx1, points2, idx2);
+                case PCTSignatures::HEURISTIC:
+                    return heuristicSimilarity(distancefunction, similarityParameter, points1, idx1, points2, idx2);
+                default:
+                    CV_Error(Error::StsNotImplemented, "Similarity function not implemented!");
+                    return -1;
+                }
+            }
+        }
+    }
+}
+
+#endif
+
+#endif

modules/xfeatures2d/src/pct_signatures_sqfd.cpp

+/*
+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
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez 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:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions 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.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may 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 copyright holders 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.
+*/
+
+/*
+Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
+    based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
+
+References:
+    Martin Krulis, Jakub Lokoc, Tomas Skopal.
+    Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
+    Multimedia tools and applications, 75(13), pp.: 80718103, Springer, ISSN: 1380-7501, 2016
+
+    Christian Beecks, Merih Seran Uysal, Thomas Seidl.
+    Signature quadratic form distance.
+    In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
+    ACM, 2010.
+*/
+#include "precomp.hpp"
+
+#include "pct_signatures/constants.hpp"
+#include "pct_signatures/similarity.hpp"
+
+namespace cv
+{
+    namespace xfeatures2d
+    {
+        namespace pct_signatures
+        {
+            class PCTSignaturesSQFD_Impl : public PCTSignaturesSQFD
+            {
+            public:
+                PCTSignaturesSQFD_Impl(
+                    const int distanceFunction,
+                    const int similarityFunction,
+                    const float similarityParameter)
+                    : mDistanceFunction(distanceFunction),
+                    mSimilarityFunction(similarityFunction),
+                    mSimilarityParameter(similarityParameter)
+                {
+
+                }
+
+
+                float computeQuadraticFormDistance(
+                    InputArray _signature0,
+                    InputArray _signature1) const;
+
+                void computeQuadraticFormDistances(
+                    const Mat& sourceSignature,
+                    const std::vector<Mat>& imageSignatures,
+                    std::vector<float>& distances) const;
+
+
+            private:
+                int mDistanceFunction;
+                int mSimilarityFunction;
+                float mSimilarityParameter;
+
+                float computePartialSQFD(
+                    const Mat& signature0,
+                    const Mat& signature1) const;
+
+            };
+
+
+            /**
+            * @brief Class implementing parallel computing of SQFD distance for multiple images.
+            */
+            class Parallel_computeSQFDs : public ParallelLoopBody
+            {
+            private:
+                const PCTSignaturesSQFD* mPctSignaturesSQFDAlgorithm;
+                const Mat* mSourceSignature;
+                const std::vector<Mat>* mImageSignatures;
+                std::vector<float>* mDistances;
+
+            public:
+                Parallel_computeSQFDs(
+                    const PCTSignaturesSQFD* pctSignaturesSQFDAlgorithm,
+                    const Mat* sourceSignature,
+                    const std::vector<Mat>* imageSignatures,
+                    std::vector<float>* distances)
+                    : mPctSignaturesSQFDAlgorithm(pctSignaturesSQFDAlgorithm),
+                    mSourceSignature(sourceSignature),
+                    mImageSignatures(imageSignatures),
+                    mDistances(distances)
+                {
+                    mDistances->resize(imageSignatures->size());
+                }
+
+                void operator()(const Range& range) const
+                {
+                    if (mSourceSignature->empty())
+                    {
+                        CV_Error(Error::StsBadArg, "Source signature is empty!");
+                    }
+
+                    for (int i = range.start; i < range.end; i++)
+                    {
+                        if (mImageSignatures[i].empty())
+                        {
+                            CV_Error_(Error::StsBadArg, ("Signature ID: %d is empty!", i));
+                        }
+
+                        (*mDistances)[i] = mPctSignaturesSQFDAlgorithm->computeQuadraticFormDistance(
+                            *mSourceSignature, (*mImageSignatures)[i]);
+                    }
+                }
+            };
+
+
+            float PCTSignaturesSQFD_Impl::computeQuadraticFormDistance(
+                      InputArray _signature0,
+                      InputArray _signature1) const
+            {
+                // check input
+                if (_signature0.empty() || _signature1.empty())
+                {
+                    CV_Error(Error::StsBadArg, "Empty signature!");
+                }
+
+                Mat signature0 = _signature0.getMat();
+                Mat signature1 = _signature1.getMat();
+
+                if (signature0.cols != SIGNATURE_DIMENSION || signature1.cols != SIGNATURE_DIMENSION)
+                {
+                    CV_Error_(Error::StsBadArg, ("Signature dimension must be %d!", SIGNATURE_DIMENSION));
+                }
+
+                if (signature0.rows <= 0 || signature1.rows <= 0)
+                {
+                    CV_Error(Error::StsBadArg, "Signature count must be greater than 0!");
+                }
+
+                // compute sqfd
+                float result = 0;
+                result += computePartialSQFD(signature0, signature0);
+                result += computePartialSQFD(signature1, signature1);
+                result -= computePartialSQFD(signature0, signature1) * 2;
+
+                return sqrt(result);
+            }
+
+            void PCTSignaturesSQFD_Impl::computeQuadraticFormDistances(
+                      const Mat& sourceSignature,
+                      const std::vector<Mat>& imageSignatures,
+                      std::vector<float>& distances) const
+            {
+                parallel_for_(Range(0, (int)imageSignatures.size()),
+                    Parallel_computeSQFDs(this, &sourceSignature, &imageSignatures, &distances));
+            }
+
+            float PCTSignaturesSQFD_Impl::computePartialSQFD(
+                      const Mat& signature0,
+                      const Mat& signature1) const
+            {
+                float result = 0;
+                for (int i = 0; i < signature0.rows; i++)
+                {
+                    for (int j = 0; j < signature1.rows; j++)
+                    {
+                        result += signature0.at<float>(i, WEIGHT_IDX) * signature1.at<float>(j, WEIGHT_IDX)
+                            * computeSimilarity(mDistanceFunction, mSimilarityFunction, mSimilarityParameter, signature0, i, signature1, j);
+                    }
+                }
+                return result;
+            }
+
+
+
+        }// end of namespace pct_signatures
+
+
+        Ptr<PCTSignaturesSQFD> PCTSignaturesSQFD::create(
+            const int distanceFunction,
+            const int similarityFunction,
+            const float similarityParameter)
+        {
+            return makePtr<pct_signatures::PCTSignaturesSQFD_Impl>(distanceFunction, similarityFunction, similarityParameter);
+        }
+
+    }
+}