OpenCV中更稳更快的边缘检测方法，快速查找线、圆、椭圆--EdgeDrawing-C++代码

计算机视觉之家看到快速圆检测Edge Drawing，其效果比霍夫要好，速度更快（具体效果可以参考视觉之家的文章），上面C++代码不全，那么好的检测效果国内资料竟然那么少，后在opencv的开发文档中找到了C++代码，在此分享学习交流。

实战 | OpenCV中更稳更快的找圆方法--EdgeDrawing使用演示（详细步骤 + 代码）_opencv 找圆_计算机视觉之家的博客-CSDN博客

OpenCV: EdgeDrawing

OpenCV: fld_lines.cpp

#include <iostream> #include "opencv2/imgproc.hpp" #include "opencv2/ximgproc.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/highgui.hpp" using namespace std; using namespace cv; using namespace cv::ximgproc; int main(int argc, char** argv) { string in; CommandLineParser parser(argc, argv, "{@input|corridor.jpg|input image}{help h||show help message}"); if (parser.has("help")) { parser.printMessage(); return 0; } in = samples::findFile(parser.get<string>("@input")); Mat image = imread(in, IMREAD_GRAYSCALE); if( image.empty() ) { return -1; } // Create FLD detector // Param Default value Description // length_threshold 10 - Segments shorter than this will be discarded // distance_threshold 1.41421356 - A point placed from a hypothesis line // segment farther than this will be // regarded as an outlier // canny_th1 50 - First threshold for // hysteresis procedure in Canny() // canny_th2 50 - Second threshold for // hysteresis procedure in Canny() // canny_aperture_size 3 - Aperturesize for the sobel operator in Canny(). // If zero, Canny() is not applied and the input // image is taken as an edge image. // do_merge false - If true, incremental merging of segments // will be performed int length_threshold = 10; float distance_threshold = 1.41421356f; double canny_th1 = 50.0; double canny_th2 = 50.0; int canny_aperture_size = 3; bool do_merge = false; Ptr<FastLineDetector> fld = createFastLineDetector(length_threshold, distance_threshold, canny_th1, canny_th2, canny_aperture_size, do_merge); vector<Vec4f> lines; // Because of some CPU's power strategy, it seems that the first running of // an algorithm takes much longer. So here we run the algorithm 10 times // to see the algorithm's processing time with sufficiently warmed-up // CPU performance. for (int run_count = 0; run_count < 5; run_count++) { double freq = getTickFrequency(); lines.clear(); int64 start = getTickCount(); // Detect the lines with FLD fld->detect(image, lines); double duration_ms = double(getTickCount() - start) * 1000 / freq; cout << "Elapsed time for FLD " << duration_ms << " ms." << endl; } // Show found lines with FLD Mat line_image_fld(image); fld->drawSegments(line_image_fld, lines); imshow("FLD result", line_image_fld); waitKey(1); Ptr<EdgeDrawing> ed = createEdgeDrawing(); ed->params.EdgeDetectionOperator = EdgeDrawing::SOBEL; ed->params.GradientThresholdValue = 38; ed->params.AnchorThresholdValue = 8; vector<Vec6d> ellipses; for (int run_count = 0; run_count < 5; run_count++) { double freq = getTickFrequency(); lines.clear(); int64 start = getTickCount(); // Detect edges //you should call this before detectLines() and detectEllipses() ed->detectEdges(image); // Detect lines ed->detectLines(lines); double duration_ms = double(getTickCount() - start) * 1000 / freq; cout << "Elapsed time for EdgeDrawing detectLines " << duration_ms << " ms." << endl; start = getTickCount(); // Detect circles and ellipses ed->detectEllipses(ellipses); duration_ms = double(getTickCount() - start) * 1000 / freq; cout << "Elapsed time for EdgeDrawing detectEllipses " << duration_ms << " ms." << endl; } Mat edge_image_ed = Mat::zeros(image.size(), CV_8UC3); vector<vector<Point> > segments = ed->getSegments(); for (size_t i = 0; i < segments.size(); i++) { const Point* pts = &segments[i][0]; int n = (int)segments[i].size(); polylines(edge_image_ed, &pts, &n, 1, false, Scalar((rand() & 255), (rand() & 255), (rand() & 255)), 1); } imshow("EdgeDrawing detected edges", edge_image_ed); Mat line_image_ed(image); fld->drawSegments(line_image_ed, lines); // Draw circles and ellipses for (size_t i = 0; i < ellipses.size(); i++) { Point center((int)ellipses[i][0], (int)ellipses[i][1]); Size axes((int)ellipses[i][2] + (int)ellipses[i][3], (int)ellipses[i][2] + (int)ellipses[i][4]); double angle(ellipses[i][5]); Scalar color = ellipses[i][2] == 0 ? Scalar(255, 255, 0) : Scalar(0, 255, 0); ellipse(line_image_ed, center, axes, angle, 0, 360, color, 2, LINE_AA); } imshow("EdgeDrawing result", line_image_ed); waitKey(); return 0; }