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‎modules/ximgproc/include/opencv2/ximgproc.hpp

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#include "ximgproc/brightedges.hpp"
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#include "ximgproc/run_length_morphology.hpp"
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#include "ximgproc/edgepreserving_filter.hpp"
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#include "ximgproc/color_match.hpp"
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/** @defgroup ximgproc Extended Image Processing

‎modules/ximgproc/include/opencv2/ximgproc/color_match.hpp

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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#ifndef __OPENCV_COLOR_MATCH_HPP__
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#define __OPENCV_COLOR_MATCH_HPP__
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#include <opencv2/core.hpp>
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namespace cv {
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namespace ximgproc {
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//! @addtogroup ximgproc_filters
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//! @{
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/**
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* @brief creates a quaternion image.
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*
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* @param img Source 8-bit, 32-bit or 64-bit image, with 3-channel image.
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* @param qimg result CV_64FC4 a quaternion image( 4 chanels zero channel and B,G,R).
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*/
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CV_EXPORTS_W void createQuaternionImage(InputArray img, OutputArray qimg);
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/**
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* @brief calculates conjugate of a quaternion image.
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*
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* @param qimg quaternion image.
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* @param qcimg conjugate of qimg
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*/
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CV_EXPORTS_W void qconj(InputArray qimg, OutputArray qcimg);
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/**
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* @brief divides each element by its modulus.
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*
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* @param qimg quaternion image.
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* @param qnimg conjugate of qimg
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*/
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CV_EXPORTS_W void qunitary(InputArray qimg, OutputArray qnimg);
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/**
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* @brief Calculates the per-element quaternion product of two arrays
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*
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* @param src1 quaternion image.
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* @param src2 quaternion image.
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* @param dst product dst(I)=src1(I) . src2(I)
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*/
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CV_EXPORTS_W void qmultiply(InputArray src1, InputArray src2, OutputArray dst);
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/**
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* @brief Performs a forward or inverse Discrete quaternion Fourier transform of a 2D quaternion array.
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*
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* @param img quaternion image.
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* @param qimg quaternion image in dual space.
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* @param flags quaternion image in dual space. only DFT_INVERSE flags is supported
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* @param sideLeft true the hypercomplex exponential is to be multiplied on the left (false on the right ).
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*/
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CV_EXPORTS_W void qdft(InputArray img, OutputArray qimg, int flags, bool sideLeft);
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/**
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* @brief Compares a color template against overlapped color image regions.
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*
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* @param img Image where the search is running. It must be 3 channels image
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* @param templ Searched template. It must be not greater than the source image and have 3 channels
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* @param result Map of comparison results. It must be single-channel 64-bit floating-point
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*/
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CV_EXPORTS_W void colorMatchTemplate(InputArray img, InputArray templ, OutputArray result);
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}
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}
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#endif

‎modules/ximgproc/samples/color_match_template.cpp

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#include <iostream>
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#include <fstream>
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#include <opencv2/core.hpp>
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#include <opencv2/core/utility.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/ximgproc.hpp>
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#include <opencv2/ximgproc/color_match.hpp>
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using namespace std;
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using namespace cv;
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static void AddSlider(String sliderName, String windowName, int minSlider, int maxSlider, int valDefault, int *valSlider, void(*f)(int, void *), void *r)
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{
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createTrackbar(sliderName, windowName, valSlider, 1, f, r);
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setTrackbarMin(sliderName, windowName, minSlider);
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setTrackbarMax(sliderName, windowName, maxSlider);
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setTrackbarPos(sliderName, windowName, valDefault);
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}
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struct SliderData {
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Mat img;
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int thresh;
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};
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static void UpdateThreshImage(int , void *r)
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{
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SliderData *p = (SliderData*)r;
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Mat dst,labels,stats,centroids;
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threshold(p->img, dst, p->thresh, 255, THRESH_BINARY);
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connectedComponentsWithStats(dst, labels, stats, centroids, 8);
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if (centroids.rows < 10)
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{
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cout << "**********************************************************************************\n";
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for (int i = 0; i < centroids.rows; i++)
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{
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cout << dst.cols - centroids.at<double>(i, 0) << " ";
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cout << dst.rows - centroids.at<double>(i, 1) << "\n";
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}
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cout << "----------------------------------------------------------------------------------\n";
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}
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flip(dst, dst, -1);
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imshow("Max Quaternion corr",dst);
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}
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int main(int argc, char *argv[])
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{
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cv::CommandLineParser parser(argc, argv,
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"{help h | | match color image }{@colortemplate | | input color template image}{@colorimage | | input color image}");
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if (parser.has("help"))
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{
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parser.printMessage();
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return -1;
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}
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string templateName = parser.get<string>("@colortemplate");
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if (templateName.empty())
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{
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parser.printMessage();
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parser.printErrors();
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return -2;
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}
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string colorImageName = parser.get<string>("@colorimage");
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if (templateName.empty())
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{
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parser.printMessage();
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parser.printErrors();
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return -2;
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}
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Mat imgLogo = imread(templateName, IMREAD_COLOR);
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Mat imgColor = imread(colorImageName, IMREAD_COLOR);
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imshow("Image", imgColor);
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imshow("template", imgLogo);
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// OK NOW WHERE IS OPENCV LOGO ?
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Mat imgcorr;
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SliderData ps;
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ximgproc::colorMatchTemplate(imgColor, imgLogo, imgcorr);
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imshow("quaternion correlation real", imgcorr);
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normalize(imgcorr, imgcorr,1,0,NORM_MINMAX);
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imgcorr.convertTo(ps.img, CV_8U, 255);
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imshow("quaternion correlation", imgcorr);
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ps.thresh = 0;
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AddSlider("Level", "quaternion correlation", 0, 255, ps.thresh, &ps.thresh, UpdateThreshImage, &ps);
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int code = 0;
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while (code != 27)
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{
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code = waitKey(50);
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}
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waitKey(0);
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return 0;
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}

‎modules/ximgproc/src/quaternion.cpp

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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.#include "precomp.hpp"
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#include "precomp.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/ximgproc/color_match.hpp"
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using namespace std;
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namespace cv { namespace ximgproc {
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void createQuaternionImage(InputArray _img, OutputArray _qimg)
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{
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int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_CheckType(depth, depth == CV_8U || depth == CV_32F || depth == CV_64F, "Depth must be CV_8U, CV_32F or CV_64F");
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CV_Assert(_img.dims() == 2 && cn == 3);
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vector<Mat> qplane(4);
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vector<Mat> plane;
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split(_img, plane);
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qplane[0] = Mat::zeros(_img.size(), CV_64FC1);
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for (int i = 0; i < cn; i++)
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plane[i].convertTo(qplane[3-i], CV_64F);
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merge(qplane, _qimg);
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}
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void qconj(InputArray _img, OutputArray _qimg)
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{
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int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_CheckType(depth, depth == CV_32F || depth == CV_64F, "Depth must be CV_32F or CV_64F");
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CV_Assert(_img.dims() == 2 && cn == 4);
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vector<Mat> qplane(4), plane;
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split(_img, plane);
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qplane[0] = plane[0];
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qplane[1] = -plane[1];
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qplane[2] = -plane[2];
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qplane[3] = -plane[3];
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merge(qplane, _qimg);
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}
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void qunitary(InputArray _img, OutputArray _qimg)
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{
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int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_Assert((depth == CV_64F) && _img.dims() == 2 && cn == 4);
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vector<Mat> qplane(4), plane;
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split(_img, plane);
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_img.copyTo(_qimg);
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Mat qimg = _qimg.getMat();
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qimg.forEach<Vec4d>([](Vec4d &p, const int * /*position*/) -> void {
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double d = p[0] * p[0] + p[1] * p[1] + p[2] * p[2] + p[3] * p[3];
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d = 1 / sqrt(d);
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p *= d;
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});
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/*
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qplane[0] = plane[0].clone();
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qplane[1] = plane[1].clone();
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qplane[2] = plane[2].clone();
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qplane[3] = plane[3].clone();
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double *ptr0 = qplane[0].ptr<double>(0, 0), *ptr1 = qplane[1].ptr<double>(0, 0);
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double *ptr2 = qplane[2].ptr<double>(0, 0), *ptr3 = qplane[3].ptr<double>(0, 0);
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int nb = plane[0].rows*plane[0].cols;
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for (int i = 0; i < nb; i++, ptr0++, ptr1++, ptr2++, ptr3++)
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{
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double d = *ptr0 * *ptr0 + *ptr1 * *ptr1 + *ptr2 * *ptr2 + *ptr3 * *ptr3;
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d = 1 / sqrt(d);
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*ptr0 *= d;
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*ptr1 *= d;
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*ptr2 *= d;
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*ptr3 *= d;
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}
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merge(qplane, _qimg);*/
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}
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void qdft(InputArray _img, OutputArray _qimg, int flags, bool sideLeft)
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{
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CV_INSTRUMENT_REGION();
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int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_Assert(depth == CV_64F && _img.dims() == 2 && cn == 4);
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float c;
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if (sideLeft)
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c = 1; // Left qdft
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else
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c = -1; // right qdft
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vector<Mat> q;
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Mat img;
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img = _img.getMat();
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CV_Assert(getOptimalDFTSize(img.rows) == img.rows && getOptimalDFTSize(img.cols) == img.cols);
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split(img, q);
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Mat c1r;
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Mat c1i; // Imaginary part of c1 =x'
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Mat c2r; // Real part of c2 =y'
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Mat c2i; // Imaginary part of c2=z'
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c1r = q[0].clone();
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c1i = (q[1] + q[2] + q[3]) / sqrt(3);
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c2r = (q[2] - q[3]) / sqrt(2);
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c2i = c * (q[3] + q[2] - 2 * q[1]) / sqrt(6);
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vector<Mat> vc1 = { c1r,c1i }, vc2 = { c2r,c2i };
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Mat c1, c2, C1, C2;
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merge(vc1, c1);
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merge(vc2, c2);
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if (flags& DFT_INVERSE)
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{
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dft(c1, C1, DFT_COMPLEX_OUTPUT | DFT_INVERSE|DFT_SCALE);
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dft(c2, C2, DFT_COMPLEX_OUTPUT | DFT_INVERSE | DFT_SCALE);
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}
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else
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{
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dft(c1, C1, DFT_COMPLEX_OUTPUT);
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dft(c2, C2, DFT_COMPLEX_OUTPUT);
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}
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split(C1, vc1);
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split(C2, vc2);
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vector<Mat> qdft(4);
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qdft[0] = vc1[0].clone();
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qdft[1] = vc1[1] / sqrt(3) - c * 2 * vc2[1] / sqrt(6);
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qdft[2] = vc1[1] / sqrt(3) + vc2[0] / sqrt(2) + c * vc2[1] / sqrt(6);
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qdft[3] = vc1[1] / sqrt(3) - vc2[0] / sqrt(2) + c * vc2[1] / sqrt(6);
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Mat dst0;
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merge(qdft, dst0);
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dst0.copyTo(_qimg);
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}
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void qmultiply(InputArray src1, InputArray src2, OutputArray dst)
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{
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int type = src1.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_Assert(depth == CV_64F && src1.dims() == 2 && cn == 4);
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type = src2.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
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CV_Assert(depth == CV_64F && src2.dims() == 2 && cn == 4);
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vector<Mat> q3(4);
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if (src1.rows() == src2.rows() && src1.cols() == src2.cols())
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{
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vector<Mat> q1, q2;
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split(src1, q1);
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split(src2, q2);
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q3[0] = q1[0].mul(q2[0]) - q1[1].mul(q2[1]) - q1[2].mul(q2[2]) - q1[3].mul(q2[3]);
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q3[1] = q1[0].mul(q2[1]) + q1[1].mul(q2[0]) + q1[2].mul(q2[3]) - q1[3].mul(q2[2]);
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q3[2] = q1[0].mul(q2[2]) - q1[1].mul(q2[3]) + q1[2].mul(q2[0]) + q1[3].mul(q2[1]);
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q3[3] = q1[0].mul(q2[3]) + q1[1].mul(q2[2]) - q1[2].mul(q2[1]) + q1[3].mul(q2[0]);
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}
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else if (src1.rows() == 1 && src1.cols() == 1)
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{
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vector<Mat> q2;
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Vec4d q1 = src1.getMat().at<Vec4d>(0, 0);
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split(src2, q2);
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q3[0] = q1[0] * q2[0] - q1[1] * q2[1] - q1[2] * q2[2] - q1[3] * q2[3];
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q3[1] = q1[0] * q2[1] + q1[1] * q2[0] + q1[2] * q2[3] - q1[3] * q2[2];
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q3[2] = q1[0] * q2[2] - q1[1] * q2[3] + q1[2] * q2[0] + q1[3] * q2[1];
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q3[3] = q1[0] * q2[3] + q1[1] * q2[2] - q1[2] * q2[1] + q1[3] * q2[0];
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}
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else if (src2.rows() == 1 && src2.cols() == 1)
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{
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vector<Mat> q1;
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split(src1, q1);
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Vec4d q2 = src2.getMat().at<Vec4d>(0, 0);
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q3[0] = q1[0] * q2[0] - q1[1] * q2[1] - q1[2] * q2[2] - q1[3] * q2[3];
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q3[1] = q1[0] * q2[1] + q1[1] * q2[0] + q1[2] * q2[3] - q1[3] * q2[2];
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q3[2] = q1[0] * q2[2] - q1[1] * q2[3] + q1[2] * q2[0] + q1[3] * q2[1];
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q3[3] = q1[0] * q2[3] + q1[1] * q2[2] - q1[2] * q2[1] + q1[3] * q2[0];
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}
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else
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CV_Assert(src1.rows() == src2.rows() && src1.cols() == src2.cols());
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merge(q3, dst);
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}
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void colorMatchTemplate(InputArray _image, InputArray _templ, OutputArray _result)
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{
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CV_INSTRUMENT_REGION();
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Mat image = _image.getMat(), imageF;
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CV_Assert(image.channels() == 3);
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Mat colorTemplate = _templ.getMat(), colorTemplateF;
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CV_Assert(colorTemplate.channels() == 3);
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int rr = max(getOptimalDFTSize(image.rows), getOptimalDFTSize(colorTemplate.rows));
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int cc = max(getOptimalDFTSize(image.cols), getOptimalDFTSize(colorTemplate.cols));
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Mat logo(rr, cc, CV_64FC3, Scalar::all(0));
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Mat img = Mat(rr, cc, CV_64FC3, Scalar::all(0));
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colorTemplate.convertTo(colorTemplateF, CV_64F, 1 / 256.),
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colorTemplateF.copyTo(logo(Rect(0, 0, colorTemplate.cols, colorTemplate.rows)));
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image.convertTo(imageF, CV_64F, 1 / 256.);
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imageF.copyTo(img(Rect(0, 0, image.cols, image.rows)));
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Mat qimg, qlogo;
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Mat qimgFFT, qimgIFFT, qlogoFFT;
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// Create quaternion image
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createQuaternionImage(img, qimg);
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createQuaternionImage(logo, qlogo);
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// quaternion fourier transform
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qdft(qimg, qimgFFT, 0, true);
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qdft(qimg, qimgIFFT, DFT_INVERSE, true);
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qdft(qlogo, qlogoFFT, 0, false);
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double sqrtnn = sqrt(static_cast<int>(qimgFFT.rows*qimgFFT.cols));
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qimgFFT /= sqrtnn;
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qimgIFFT *= sqrtnn;
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qlogoFFT /= sqrtnn;
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Mat mu(1, 1, CV_64FC4, Scalar(0, 1, 1, 1) / sqrt(3.));
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Mat qtmp, qlogopara, qlogoortho;
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qmultiply(mu, qlogoFFT, qtmp);
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qmultiply(qtmp, mu, qtmp);
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subtract(qlogoFFT, qtmp, qlogopara);
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qlogopara = qlogopara / 2;
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subtract(qlogoFFT, qlogopara, qlogoortho);
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Mat qcross1, qcross2, cqf, cqfi;
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qconj(qimgFFT, cqf);
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qconj(qimgIFFT, cqfi);
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qmultiply(cqf, qlogopara, qcross1);
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qmultiply(cqfi, qlogoortho, qcross2);
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Mat pwsp = qcross1 + qcross2;
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Mat crossCorr, pwspUnitary;
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qunitary(pwsp, pwspUnitary);
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qdft(pwspUnitary, crossCorr, DFT_INVERSE, false);
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vector<Mat> p;
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split(crossCorr, p);
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Mat imgcorr = (p[0].mul(p[0]) + p[1].mul(p[1]) + p[2].mul(p[2]) + p[3].mul(p[3]));
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sqrt(imgcorr, _result);
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}
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}
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}

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