Opencv学习笔记--使用convexityDefects计算轮廓凸缺陷

     首先介绍今天主角：void convexityDefects(InputArray contour, InputArrayconvexhull, OutputArray convexityDefects)

     使用时注意，最后一个参数 convexityDefects 是存储 Vec4i 的向量(vector<varname>)，函数计算成功后向量的大小是轮廓凸缺陷的数量，向量每个元素Vec4i存储了4个整型数据，因为Vec4i对[]实现了重载，所以可以使用 _vectername[i][0] 来访问向量 _vactername 的第i个元素的第一个分量。再说 Vec4i 中存储的四个整形数据，Opencv 使用这四个元素表示凸缺陷，第一个名字叫做  start_index,表示缺陷在轮廓上的开始处，他的值是开始点在函数第一个参数 contour 中的下标索引；Vec4i 第二个元素的名字叫end_index， 顾名思义其对应的值就是缺陷结束处在 contour 中的下标索引； Vec4i 第三个元素 farthest_pt_index 是缺陷上距离 轮廓凸包(convexhull)最远的点；Vec4i最后的元素叫fixpt_depth，fixpt_depth/256  表示了轮廓上以 farthest_pt_index 为下标的点到 轮廓凸包的(convexhull)的距离,以像素为单位。

     All is so easy!下面就是简单的代码示例（首先计算两个轮廓的凸包，然后计算两个轮廓的凸缺陷）:

// 计算凸缺陷 convexityDefect//#include "stdafx.h"#include <opencv.hpp>#include <iostream>using namespace std;using namespace cv;int _tmain(int argc, _TCHAR* argv[]){Mat *img_01 = new Mat(400, 400, CV_8UC3);Mat *img_02 = new Mat(400, 400, CV_8UC3);*img_01 = Scalar::all(0);*img_02 = Scalar::all(0);// 轮廓点组成的数组vector<Point> points_01,points_02;// 给轮廓组赋值points_01.push_back(Point(10, 10));points_01.push_back(Point(10,390));points_01.push_back(Point(390, 390));points_01.push_back(Point(150, 250));points_02.push_back(Point(10, 10));points_02.push_back(Point(10,390));points_02.push_back(Point(390, 390));points_02.push_back(Point(250, 150));vector<int> hull_01,hull_02;// 计算凸包convexHull(points_01, hull_01, true);convexHull(points_02, hull_02, true);// 绘制轮廓for(int i=0;i < 4;++i){circle(*img_01, points_01[i], 3, Scalar(0,255,255), CV_FILLED, CV_AA);circle(*img_02, points_02[i], 3, Scalar(0,255,255), CV_FILLED, CV_AA);}// 绘制凸包轮廓CvPoint poi_01 = points_01[hull_01[hull_01.size()-1]];for(int i=0;i < hull_01.size();++i){line(*img_01, poi_01, points_01[i], Scalar(255,255,0), 1, CV_AA);poi_01 = points_01[i];}CvPoint poi_02 = points_02[hull_02[hull_02.size()-1]];for(int i=0;i < hull_02.size();++i){line(*img_02, poi_02, points_02[i], Scalar(255,255,0), 1, CV_AA);poi_02 = points_02[i];}vector<Vec4i> defects;// 如果有凸缺陷就把它画出来if( isContourConvex(points_01) ){cout<<"img_01的轮廓是凸包"<<endl;}else{cout<<"img_01的轮廓不是凸包"<<endl;convexityDefects(points_01,Mat(hull_01),defects);// 绘制缺陷cout<<"共"<<defects.size()<<"处缺陷"<<endl;for(int i=0;i < defects.size();++i){circle(*img_01, points_01[defects[i][0]], 6, Scalar(255,0,0), 2, CV_AA);circle(*img_01, points_01[defects[i][1]], 6, Scalar(255,0,0), 2, CV_AA);circle(*img_01, points_01[defects[i][2]], 6, Scalar(255,0,0), 2, CV_AA);line(*img_01, points_01[defects[i][0]], points_01[defects[i][1]], Scalar(255,0,0), 1, CV_AA);line(*img_01, points_01[defects[i][1]], points_01[defects[i][2]], Scalar(255,0,0), 1, CV_AA);line(*img_01, points_01[defects[i][2]], points_01[defects[i][0]], Scalar(255,0,0), 1, CV_AA);cout<<"第"<<i<<"缺陷<"<<points_01[defects[i][0]].x<<","<<points_01[defects[i][0]].y<<">,<"<<points_01[defects[i][1]].x<<","<<points_01[defects[i][1]].y<<">,<"<<points_01[defects[i][2]].x<<","<<points_01[defects[i][2]].y<<">到轮廓的距离为："<<defects[i][3]/256<<"px"<<endl;}defects.clear();}if( isContourConvex( points_02 ) ){cout<<"img_02的轮廓是凸包"<<endl;}else{cout<<"img_02的轮廓不是凸包"<<endl;vector<Vec4i> defects;convexityDefects(points_01,Mat(hull_01),defects);// 绘制出缺陷的轮廓for(int i=0;i < defects.size();++i){circle(*img_02, points_01[defects[i][0]], 6, Scalar(255,0,0), 2, CV_AA);circle(*img_02, points_01[defects[i][1]], 6, Scalar(255,0,0), 2, CV_AA);circle(*img_02, points_01[defects[i][2]], 6, Scalar(255,0,0), 2, CV_AA);line(*img_02, points_01[defects[i][0]], points_01[defects[i][1]], Scalar(255,0,0), 1, CV_AA);line(*img_02, points_01[defects[i][1]], points_01[defects[i][2]], Scalar(255,0,0), 1, CV_AA);line(*img_02, points_01[defects[i][2]], points_01[defects[i][0]], Scalar(255,0,0), 1, CV_AA);// 因为 img_02 没有缺陷所以就懒的写那些输出代码了}defects.clear();}imshow("img_01 的轮廓和凸包：", *img_01);imshow("img_02 的轮廓和凸包：", *img_02);cvWaitKey();return 0;}