OpenCV学习(30) 轮廓defects

     上一篇教程中，我们学习了如何计算轮廓的凸包，其实对一个轮廓而言，可能它的凸包和它本身是重合的，也有可能不是重合的。比如下面左边图像的轮廓本身就是凸包，而右边图像的轮廓则不是。我们可以通过函数bool isContourConvex(InputArray contour)，来判定一个轮廓是否是凸包，是的话返回true，否则false[注意测试的轮廓必须是简单轮廓，没有自交叉之类的]。

      对一个非凸包的轮廓而言，它包括一系列的凹陷区域，这些区域称作defect，比如下面手轮廓中，包括6个defect区域。在OpenCV中，我们用下面的结构来定义defect。

struct CvConvexityDefect { CvPoint* start; // 轮廓中defect的起点 CvPoint* end; // 轮廓中defect的终点 CvPoint* depth_point; // defect中到凸包最远的点 float depth; // 最远点和凸包之间的距离};

    在OpenCV中，我们通过函数

void convexityDefects(InputArray contour, InputArray convexhull, OutputArray convexityDefects)

得到轮廓的凸包，其中第一个参数和第二个参数是轮廓以及轮廓对应的凸包，注意凸包应该使用vector<int>这样的索引方式表示。第三个参数为返回的defect点集。

下面我们看下检测轮廓defects的代码：

#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;RNG rng(12345);

int main( int argc, char** argv ){//装入图像    src = imread("../hand1.jpg", 1 );

//转化为灰度图像    cvtColor( src, src_gray, CV_BGR2GRAY );//blur( src_gray, src_gray, Size(3,3) );    namedWindow( "image");    imshow( "image", src_gray );

Mat threshold_output;    vector<vector<Point> > contours;    vector<Vec4i> hierarchy;

//得到二值图    threshold( src_gray, threshold_output, 200, 255, THRESH_BINARY );

//查找轮廓    findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );    printf("轮廓数目:%d\n", contours.size());/// Find the convex hull object for each contour    vector<vector<Point> >hull( contours.size() );for( int i = 0; i < contours.size(); i++ )    {  convexHull( Mat(contours[i]), hull[i], false ); }

/// Draw contours + hull results    Mat drawing = Mat::zeros( threshold_output.size(), CV_8UC3 );int area = 0; //轮廓索引int k = 0;int i;for(i = 0; i< contours.size(); i++ )    {        Scalar color1 = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );        drawContours( drawing, contours, i, color1, 1, 8, vector<Vec4i>(), 0, Point() );        Scalar color2 = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );        drawContours( drawing, hull, i, color2, 1, 8, vector<Vec4i>(), 0, Point() );int tt = contourArea(contours[i]);        printf("轮廓面积%d = %d\n", i, tt);if( tt > area)        {            area = contourArea(contours[i]);            k = i;        }

}

vector<Point> hull1;    hull1 = hull[1];for(i = 0; i< hull1.size(); i++ )    {        printf("point %d, %d, %d\n", i, hull1[i].x, hull1[i].y);        circle(drawing, hull1[i], 6, Scalar(255,0,0), 3, CV_AA);      }

int j;for(j=0; j< contours.size(); j++)    {//如果没有defects或者轮廓小于三个点，则continueif( isContourConvex(contours[j])|| contours[j].size()<3) continue;

vector<int> convexHull_IntIdx;        vector<Vec4i> defects;if (contours[j].size() >3 )        {            convexHull(contours[j], convexHull_IntIdx, true);            convexityDefects(contours[j], convexHull_IntIdx, defects);        }    

for(i=0;i < defects.size();++i)          {              Matx<int,4,1> defectVector = defects[i];            vector<Point> contours1 =contours[j];            Point point1 = contours1[defectVector.val[0]];//开始点            Point point2 = contours1[defectVector.val[1]];//结束点            Point point3 = contours1[defectVector.val[2]];//深度点float dist = defectVector.val[3];            printf("dist: %f \n", dist);//if ( defectVector.val[3] <= 1000 ) { continue; } // skip defects that are shorter than 100 pixel            circle(drawing, point1, 3, Scalar(255,255,0), 2, CV_AA);            circle(drawing, point2, 8, Scalar(0,255,0), 2, CV_AA);            circle(drawing, point3, 3, Scalar(0,255,255), 2, CV_AA);

}      }/// Show in a window    namedWindow( "Hull demo");    imshow( "Hull demo", drawing );

waitKey(0);return(0);}

程序执行之后界面如下，注意左下有图中

程序代码：工程FirstOpenCV25