// The "Square Detector" program. // It loads several images sequentially and tries to find squares in // each image #include "opencv2/core.hpp" #include "opencv2/imgproc.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/highgui.hpp" #include using namespace cv; using namespace std; static void help(const char* programName) { cout << "\nA program using pyramid scaling, Canny, contours and contour simplification\n" "to find squares in a list of images (pic1-6.png)\n" "Returns sequence of squares detected on the image.\n" "Call:\n" "./" << programName << " [file_name (optional)]\n" "Using OpenCV version " << CV_VERSION << "\n" << endl; } int thresh = 50, N = 11; const char* wndname = "Square Detection Demo"; // helper function: // finds a cosine of angle between vectors // from pt0->pt1 and from pt0->pt2 static double angle( Point pt1, Point pt2, Point pt0 ) { double dx1 = pt1.x - pt0.x; double dy1 = pt1.y - pt0.y; double dx2 = pt2.x - pt0.x; double dy2 = pt2.y - pt0.y; return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10); } // returns sequence of squares detected on the image. static void findSquares( const Mat& image, vector >& squares ) { squares.clear(); Mat pyr, timg, gray0(image.size(), CV_8U), gray; // down-scale and upscale the image to filter out the noise pyrDown(image, pyr, Size(image.cols/2, image.rows/2)); pyrUp(pyr, timg, image.size()); vector > contours; // find squares in every color plane of the image for( int c = 0; c < 3; c++ ) { int ch[] = {c, 0}; mixChannels(&timg, 1, &gray0, 1, ch, 1); // try several threshold levels for( int l = 0; l < N; l++ ) { // hack: use Canny instead of zero threshold level. // Canny helps to catch squares with gradient shading if( l == 0 ) { // apply Canny. Take the upper threshold from slider // and set the lower to 0 (which forces edges merging) Canny(gray0, gray, 0, thresh, 5); // dilate canny output to remove potential // holes between edge segments dilate(gray, gray, Mat(), Point(-1,-1)); } else { // apply threshold if l!=0: // tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 gray = gray0 >= (l+1)*255/N; } // find contours and store them all as a list findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE); vector approx; // test each contour for( size_t i = 0; i < contours.size(); i++ ) { // approximate contour with accuracy proportional // to the contour perimeter approxPolyDP(contours[i], approx, arcLength(contours[i], true)*0.02, true); // square contours should have 4 vertices after approximation // relatively large area (to filter out noisy contours) // and be convex. // Note: absolute value of an area is used because // area may be positive or negative - in accordance with the // contour orientation if( approx.size() == 4 && fabs(contourArea(approx)) > 1000 && isContourConvex(approx) ) { double maxCosine = 0; for( int j = 2; j < 5; j++ ) { // find the maximum cosine of the angle between joint edges double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1])); maxCosine = MAX(maxCosine, cosine); } // if cosines of all angles are small // (all angles are ~90 degree) then write quandrange // vertices to resultant sequence if( maxCosine < 0.3 ) squares.push_back(approx); } } } } } int main(int argc, char** argv) { const char* names[] = { "pic1.png", "pic2.png", "pic3.png", "pic4.png", "pic5.png", "pic6.png", 0 }; help(argv[0]); if( argc > 1) { names[0] = argv[1]; names[1] = 0; } for( int i = 0; names[i] != 0; i++ ) { string filename = samples::findFile(names[i]); Mat image = imread(filename, IMREAD_COLOR); if( image.empty() ) { cout << "Couldn't load " << filename << endl; continue; } vector > squares; findSquares(image, squares); polylines(image, squares, true, Scalar(0, 255, 0), 3, LINE_AA); imshow(wndname, image); int c = waitKey(); if( c == 27 ) break; } return 0; }