opencv 凹凸性检测 和 缺陷分析
opencv 凹凸性检测 和 缺陷分析
原文链接：https://blog.csdn.net/lichengyu/article/details/38392473
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本文链接：https://blog.csdn.net/lichengyu/article/details/38392473
一 概念：
Convexity hull, Convexity defects
如上图所示，黑色的轮廓线为convexity hull, 而convexity hull与手掌之间的部分为convexity defects. 每个convexity defect区域有四个特征量：起始点（startPoint），结束点(endPoint)，距离convexity hull最远点(farPoint)，最远点到convexity hull的距离(depth)。
二．OpenCV中的相关函数
void convexityDefects(InputArray contour, InputArray convexhull, OutputArrayconvexityDefects)
参数：
coutour: 输入参数，检测到的轮廓，可以调用findContours函数得到；
convexhull: 输入参数，检测到的凸包，可以调用convexHull函数得到。注意，convexHull函数可以得到vector<vector<Point>>和vector<vector<int>>两种类型结果，这里的convexhull应该为vector<vector<int>>类型，否则通不过ASSERT检查；
convexityDefects：输出参数，检测到的最终结果，应为vector<vector<Vec4i>>类型，Vec4i存储了起始点（startPoint），结束点(endPoint)，距离convexity hull最远点(farPoint)以及最远点到convexity hull的距离(depth)
三．代码
//http://docs.opencv.org/doc/tutorials/imgproc/shapedescriptors/hull/hull.html//http://www.codeproject.com/Articles/782602/Beginners-guide-to-understand-Fingertips-counting #include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #include <iostream> #include <stdio.h> #include <stdlib.h> using namespace cv; using namespace std; Mat src; Mat src_gray; int thresh = 100; int max_thresh = 255; RNG rng(12345); /// Function header void thresh_callback(int, void* ); /** @function main */int main( int argc, char** argv ) { /// Load source image and convert it to gray src = imread( argv[1], 1 ); /// Convert image to gray and blur it cvtColor( src, src_gray, CV_BGR2GRAY ); blur( src_gray, src_gray, Size(3,3) ); /// Create Window char* source_window = "Source"; namedWindow( source_window, CV_WINDOW_AUTOSIZE ); imshow( source_window, src ); createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback ); thresh_callback( 0, 0 ); waitKey(0); return(0); } /** @function thresh_callback */ void thresh_callback(int, void* ) { Mat src_copy = src.clone(); Mat threshold_output; vector<vector<Point> > contours; vector<Vec4i> hierarchy; /// Detect edges using Threshold threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY ); /// Find contours findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ); /// Find the convex hull object for each contour vector<vector<Point> >hull( contours.size() ); // Int type hull vector<vector<int>> hullsI( contours.size() ); // Convexity defects vector<vector<Vec4i>> defects( contours.size() ); for( size_t i = 0; i < contours.size(); i++ ) { convexHull( Mat(contours[i]), hull[i], false ); // find int type hull convexHull( Mat(contours[i]), hullsI[i], false ); // get convexity defects convexityDefects(Mat(contours[i]),hullsI[i], defects[i]); } /// Draw contours + hull results Mat drawing = Mat::zeros( threshold_output.size(), CV_8UC3 ); for( size_t i = 0; i< contours.size(); i++ ) { Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) ); drawContours( drawing, contours, i, color, 1, 8, vector<Vec4i>(), 0, Point() ); drawContours( drawing, hull, i, color, 1, 8, vector<Vec4i>(), 0, Point() ); // draw defects size_t count = contours[i].size(); std::cout<<"Count : "<<count<<std::endl; if( count < 300 ) continue; vector<Vec4i>::iterator d =defects[i].begin(); while( d!=defects[i].end() ) { Vec4i& v=(*d); //if(IndexOfBiggestContour == i) { int startidx=v[0]; Point ptStart( contours[i][startidx] ); // point of the contour where the defect begins int endidx=v[1]; Point ptEnd( contours[i][endidx] ); // point of the contour where the defect ends int faridx=v[2]; Point ptFar( contours[i][faridx] );// the farthest from the convex hull point within the defect int depth = v[3] / 256; // distance between the farthest point and the convex hull if(depth > 20 && depth < 80) { line( drawing, ptStart, ptFar, CV_RGB(0,255,0), 2 ); line( drawing, ptEnd, ptFar, CV_RGB(0,255,0), 2 ); circle( drawing, ptStart, 4, Scalar(255,0,100), 2 ); circle( drawing, ptEnd, 4, Scalar(255,0,100), 2 ); circle( drawing, ptFar, 4, Scalar(100,0,255), 2 ); } /*printf("start(%d,%d) end(%d,%d), far(%d,%d)\n", ptStart.x, ptStart.y, ptEnd.x, ptEnd.y, ptFar.x, ptFar.y);*/ } d++; } } /// Show in a window namedWindow( "Hull demo", CV_WINDOW_AUTOSIZE ); imshow( "Hull demo", drawing ); //imwrite("convexity_defects.jpg", drawing); }四．结果
原图
Convexity defects图，蓝色点是convexity defects的起始点和结束点，红色点是最远点。（为什么有的起始点和结束点中间没有最远点呢？因为只画出了depth范围在20到80之间的convexity defects的起始点、结束点和最远点）
五．参考
[1] Gary Bradski, Adrian Kaehler. Learning OpenCV: Computer Vision with the OpenCV Library. Page258~259.
[2] http://docs.opencv.org/doc/tutorials/imgproc/shapedescriptors/hull/hull.html
[3] http://www.codeproject.com/Articles/782602/Beginners-guide-to-understand-Fingertips-counting