opencv学习之路（21）、模板匹配及应用

一、模板匹配概念

二、单模板匹配

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

 void main()
 {
     Mat temp=imread("E://mu.jpg");
     Mat src=imread("E://lena.jpg");
     Mat dst=src.clone();
     imshow("temp",temp);

     int width=src.cols-temp.cols+;//result宽度
     int height=src.rows-temp.rows+;//result高度

     Mat result(height,width,CV_32FC1);//创建结果映射图像
     //matchTemplate(srcImg, templateImg, resultImg, CV_TM_SQDIFF); //平方差匹配法(最好匹配0)
     //matchTemplate(srcImg, templateImg, resultImg, CV_TM_SQDIFF_NORMED); //归一化平方差匹配法(最好匹配0)
     //matchTemplate(srcImg, templateImg, resultImg, CV_TM_CCORR); //相关匹配法(最坏匹配0)
     //matchTemplate(srcImg, templateImg, resultImg, CV_TM_CCORR_NORMED); //归一化相关匹配法(最坏匹配0)
     //matchTemplate(srcImg, templateImg, resultImg, CV_TM_CCOEFF); //系数匹配法(最好匹配1)
     matchTemplate(src,temp,result,CV_TM_CCOEFF_NORMED);//化相关系数匹配,最佳值1
     imshow("result",result);
     normalize(result,result,,,NORM_MINMAX,-);//归一化到0-1范围

     double minValue,maxValue;
     Point minLoc,maxLoc;
     minMaxLoc(result,&minValue,&maxValue,&minLoc,&maxLoc);
     cout<<"minValue="<<minValue<<endl;
     cout<<"maxValue="<<maxValue<<endl;

     rectangle(dst,maxLoc,Point(maxLoc.x+temp.cols,maxLoc.y+temp.rows),Scalar(,,),,);
     imshow("dst",dst);

     waitKey();
 }

注意：result的长宽正好是原图-模板图的长宽，result图中白亮程度表示匹配程度

三、视频模板匹配

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

 void main()
 {
     Mat frame,resultImg;
     Mat templateImg = imread("E://green.jpg");
     VideoCapture cap("E://1.mp4");
     if(!cap.isOpened())
         return;
     int resultImg_cols,resultImg_rows;

     while()
     {
         cap>>frame;
         if(frame.empty())    break;
         Mat showImg = frame.clone();
         resultImg_cols = frame.cols -  templateImg.cols + ;
         resultImg_rows = frame.rows -  templateImg.rows + ;
         resultImg.create(resultImg_cols, resultImg_rows, CV_32FC1);
         matchTemplate(frame, templateImg, resultImg, CV_TM_CCOEFF_NORMED); //化相关系数匹配法(最好匹配1)
         normalize(resultImg, resultImg, , , NORM_MINMAX);

         double minValue, maxValue;
         Point minLoc, maxLoc;
         Point matchLoc;

         minMaxLoc(resultImg, &minValue, &maxValue, &minLoc, &maxLoc);
         cout<<"max_value= "<<maxValue<<endl;
         //cout<<"min_value= "<<minValue<<endl;
         if(maxValue>=0.7)
             rectangle(showImg, maxLoc, Point(maxLoc.x + templateImg.cols, maxLoc.y + templateImg.rows), Scalar(, , ), );
         imshow("frame", frame);
         imshow("result", showImg);
         if( == waitKey())
             break;
     }
     destroyAllWindows();

     waitKey();
 }

四、多模板匹配（没懂/(ㄒoㄒ)/~~）

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

 void main()
 {
     Mat srcImg = imread("E://src.png");
     Mat templateImg = imread("E://temp.png");
     Mat resultImg;
     Mat showImg = srcImg.clone();

     int resultImg_cols = srcImg.cols -  templateImg.cols + ;
     int resultImg_rows = srcImg.rows -  templateImg.rows + ;

     resultImg.create(resultImg_cols, resultImg_rows, CV_32FC1);
     matchTemplate(srcImg, templateImg, resultImg, CV_TM_CCOEFF_NORMED); //化相关系数匹配法(最好匹配1)
     normalize(resultImg, resultImg, , , NORM_MINMAX);
     Mat midImg = resultImg.clone();

     //多目标模板匹配---方法一
     /*double matchValue;
     int count0=0;
     int tempW=0, tempH=0;
     char matchRate[10];

     for(int i=0; i<resultImg_rows; i++)
     {
         for(int j=0; j<resultImg_cols; j++)
         {
             matchValue = resultImg.at<float>(i, j);
             sprintf(matchRate, "%0.2f", matchValue);
             if(matchValue>=0.85 && (abs(j - tempW)>5) && (abs(i - tempH)>5) )
             {
                 count0++;
                 putText(showImg, matchRate, Point(j-5, i-5), CV_FONT_HERSHEY_COMPLEX, 1, Scalar(0, 0, 255), 1);
                 rectangle(showImg, Point(j, i), Point(j + templateImg.cols, i + templateImg.rows), Scalar(0, 255, 0), 2);
                 tempW = j;
                 tempH = i;
             }
         }
     }
     cout<<"count="<<count0<<endl;
     imshow("resultImg", resultImg);
     imshow("dst", showImg);*/ 

     //多目标模板匹配---方法二
     double minValue, maxValue;
     Point minLoc, maxLoc;
     Point matchLoc;
     char matchRate[];

     for(int i=; i<; i++)
     {
         int startX = maxLoc.x - ;
         int startY = maxLoc.y - ;
         int endX = maxLoc.x + ;
         int endY = maxLoc.y + ;
         if(startX< || startY<)
         {
             startX = ;
             startY = ;
         }
          if(endX > resultImg.cols -  || endY > resultImg.rows - )
         {
             endX = resultImg.cols - ;
             endY = resultImg.rows- ;
         }
          Mat temp = Mat::zeros(endX - startX, endY - startY, CV_32FC1);
          //Mat ROI = resultImg(Rect(Point(startX, startY), temp.cols, temp.rows));
          temp.copyTo(resultImg(Rect(startX, startY, temp.cols, temp.rows)));
          minMaxLoc(resultImg, &minValue, &maxValue, &minLoc, &maxLoc);
          if(maxValue<0.8)    break;

          cout<<"max_value= "<<maxValue<<endl;
          sprintf(matchRate, "%0.2f", maxValue);
          putText(showImg, matchRate, Point(maxLoc.x - , maxLoc.y - ), CV_FONT_HERSHEY_COMPLEX, , Scalar(, , ), );
          rectangle(showImg, maxLoc, Point(maxLoc.x + templateImg.cols, maxLoc.y + templateImg.rows), Scalar(, , ), );

     }
     imshow("midImg", midImg);
     imshow("resultImg", resultImg);
     imshow("dst", showImg);

     waitKey();
 }