opencv学习之路（28）、轮廓查找与绘制（七）——位置关系及轮廓匹配

一、点与轮廓的距离及位置关系

 #include "opencv2/opencv.hpp"
 #include <iostream>
 using namespace std;
 using namespace cv;

 void main()
 {
     //计算点到轮廓的距离与位置关系
     Mat srcImg = imread("E://00.png");
     imshow("src", srcImg);

     Mat dstImg = srcImg.clone();
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY);
     imshow("threshold", srcImg);

     //查找轮廓
     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);//TREE:提取所有轮廓    NONE：画出轮廓所有点
     cout << "contours.size()=" << contours.size() << endl;
     for (int i = ; i < contours.size(); i++)//遍历每个轮廓
     {
         for (int j = ; j < contours[i].size(); j++)//遍历轮廓每个点
         {
             cout << "(" << contours[i][j].x << "," << contours[i][j].y << ")" << endl;
         }
     }

     double a0 = pointPolygonTest(contours[], Point(, ), true);//点到轮廓的最短距离
     double b0 = pointPolygonTest(contours[], Point(, ), false);//点与轮廓的位置关系：-1表示外部；0表示在轮廓上；1表示轮廓内部
     cout << "a0=" << a0 << endl;
     cout << "b0=" << b0 << endl;
     waitKey();
 }

a0之所以是负数，是因为点在轮廓外部

二、轮廓的矩

轮廓矩的介绍：

http://blog.csdn.net/cp32212116/article/details/38374015
http://blog.csdn.net/huixingshao/article/details/42060231

 #include "opencv2/opencv.hpp"
 #include <iostream>
 using namespace std;
 using namespace cv;

 void main()
 {
     Mat srcImg = imread("E://00.png");
     imshow("src", srcImg);

     Mat dstImg = srcImg.clone();
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY);
     //imshow("threshold", srcImg);

     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE);
     cout << "contours.size()=" << contours.size() << endl;
     Moments moment0 = moments(contours[], false);
     cout << moment0.m00<< endl;
     waitKey();
 }

三、形状匹配--matchShapes()

注意与模板匹配matchTemplate()相区分。形状匹配对于旋转、尺度、位移都能适应。

 #include "opencv2/opencv.hpp"
 #include <iostream>
 #include <iomanip>
 using namespace std;
 using namespace cv;

 void main()
 {
     Mat srcImg = imread("1.jpg");  //模板图像
     imshow("src", srcImg);
     cvtColor(srcImg, srcImg, CV_BGR2GRAY);
     threshold(srcImg, srcImg, , , CV_THRESH_BINARY);
     vector<vector<Point>> contours;
     vector<Vec4i> hierarcy;
     findContours(srcImg, contours, hierarcy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

     Mat srcImg2 = imread("2.jpg");  //待测试图片
     imshow("src2", srcImg2);
     Mat dstImg = srcImg2.clone();
     cvtColor(srcImg2, srcImg2, CV_BGR2GRAY);
     threshold(srcImg2, srcImg2, , , CV_THRESH_BINARY);
     vector<vector<Point>> contours2;
     vector<Vec4i> hierarcy2;
     findContours(srcImg2, contours2, hierarcy2, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
     while ()
     {
         for (int i = ; i<contours2.size(); i++)
         {
             double matchRate = matchShapes(contours[], contours2[i], CV_CONTOURS_MATCH_I1, 0.0);//形状匹配:值越小越相似
             cout << "index=" << i << "---" << setiosflags(ios::fixed) << matchRate << endl;//setiosflags(ios::fixed)是用定点方式表示实数，保留相同位数，相同格式输出
             if (matchRate <= 0.1)
                 drawContours(dstImg, contours2, i, Scalar(, , ), , );
             imshow("dst", dstImg);
             /*char key = waitKey();
             if (key == 27)
                 break;*/
         }
         break;
     }
     waitKey();
 }