/** * @file HoughLines_Demo.cpp * @brief Demo code for Hough Transform * @author OpenCV team */ #include "opencv2/imgcodecs.hpp" #include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #include <iostream> #include <stdio.h> using namespace cv; using namespace std; /// Global variables /** General variables */ Mat src, edges; Mat src_gray; Mat standard_hough, probabilistic_hough; int min_threshold = 50; int max_trackbar = 150; const char* standard_name = "Standard Hough Lines Demo"; const char* probabilistic_name = "Probabilistic Hough Lines Demo"; int s_trackbar = max_trackbar; int p_trackbar = max_trackbar; /// Function Headers void help(); void Standard_Hough( int, void* ); void Probabilistic_Hough( int, void* ); /** * @function main */ int main( int, char** argv ) { /// Read the image src = imread( argv[1], 1 ); if( src.empty() ) { help(); return -1; } /// Pass the image to gray cvtColor( src, src_gray, COLOR_RGB2GRAY ); /// Apply Canny edge detector Canny( src_gray, edges, 50, 200, 3 ); /// Create Trackbars for Thresholds char thresh_label[50]; sprintf( thresh_label, "Thres: %d + input", min_threshold ); namedWindow( standard_name, WINDOW_AUTOSIZE ); createTrackbar( thresh_label, standard_name, &s_trackbar, max_trackbar, Standard_Hough); namedWindow( probabilistic_name, WINDOW_AUTOSIZE ); createTrackbar( thresh_label, probabilistic_name, &p_trackbar, max_trackbar, Probabilistic_Hough); /// Initialize Standard_Hough(0, 0); Probabilistic_Hough(0, 0); waitKey(0); return 0; } /** * @function help * @brief Indications of how to run this program and why is it for */ void help() { printf("\t Hough Transform to detect lines \n "); printf("\t---------------------------------\n "); printf(" Usage: ./HoughLines_Demo <image_name> \n"); } /** * @function Standard_Hough */ void Standard_Hough( int, void* ) { vector<Vec2f> s_lines; cvtColor( edges, standard_hough, COLOR_GRAY2BGR ); /// 1. Use Standard Hough Transform HoughLines( edges, s_lines, 1, CV_PI/180, min_threshold + s_trackbar, 0, 0 ); /// Show the result for( size_t i = 0; i < s_lines.size(); i++ ) { float r = s_lines[i][0], t = s_lines[i][1]; double cos_t = cos(t), sin_t = sin(t); double x0 = r*cos_t, y0 = r*sin_t; double alpha = 1000; Point pt1( cvRound(x0 + alpha*(-sin_t)), cvRound(y0 + alpha*cos_t) ); Point pt2( cvRound(x0 - alpha*(-sin_t)), cvRound(y0 - alpha*cos_t) ); line( standard_hough, pt1, pt2, Scalar(255,0,0), 3, LINE_AA); } imshow( standard_name, standard_hough ); } /** * @function Probabilistic_Hough */ void Probabilistic_Hough( int, void* ) { vector<Vec4i> p_lines; cvtColor( edges, probabilistic_hough, COLOR_GRAY2BGR ); /// 2. Use Probabilistic Hough Transform HoughLinesP( edges, p_lines, 1, CV_PI/180, min_threshold + p_trackbar, 30, 10 ); /// Show the result for( size_t i = 0; i < p_lines.size(); i++ ) { Vec4i l = p_lines[i]; line( probabilistic_hough, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(255,0,0), 3, LINE_AA); } imshow( probabilistic_name, probabilistic_hough ); }