66 lines
1.5 KiB
C++
66 lines
1.5 KiB
C++
#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/contrib/contrib.hpp"
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#include <iostream>
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using namespace cv;
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using namespace std;
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void help()
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{
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cout <<
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"\nThis program demonstrates Chamfer matching -- computing a distance between an \n"
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"edge template and a query edge image.\n"
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"Usage:\n"
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"./chamfer <image edge map> <template edge map>,"
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" By default the inputs are logo_in_clutter.png logo.png\n" << endl;
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return;
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}
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int main( int argc, char** argv )
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{
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if( argc != 3 )
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{
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help();
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return 0;
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}
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Mat img = imread(argc == 3 ? argv[1] : "logo_in_clutter.png", 0);
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Mat cimg;
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cvtColor(img, cimg, CV_GRAY2BGR);
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Mat tpl = imread(argc == 3 ? argv[2] : "logo.png", 0);
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// if the image and the template are not edge maps but normal grayscale images,
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// you might want to uncomment the lines below to produce the maps. You can also
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// run Sobel instead of Canny.
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// Canny(img, img, 5, 50, 3);
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// Canny(tpl, tpl, 5, 50, 3);
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vector<vector<Point> > results;
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vector<float> costs;
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int best = chamerMatching( img, tpl, results, costs );
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if( best < 0 )
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{
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cout << "matching not found\n";
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return 0;
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}
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size_t i, n = results[best].size();
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for( i = 0; i < n; i++ )
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{
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Point pt = results[best][i];
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if( pt.inside(Rect(0, 0, cimg.cols, cimg.rows)) )
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cimg.at<Vec3b>(pt) = Vec3b(0, 255, 0);
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}
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imshow("result", cimg);
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waitKey();
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return 0;
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}
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