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