C++:void matchTemplate(InputArray image, InputArray templ, OutputArray result, int method)

image:  搜尋物件影象 It must be 8-bit or 32-bit floating-point.

templ:模板影象，小於image，並且和image有相同的資料型別

result:比較結果 必須是單通單32位浮點數

method：比較演算法總共有六種如下所示

method=CV_TM_SQDIFF

• method=CV_TM_SQDIFF_NORMED

  

• method=CV_TM_CCORR

  

• method=CV_TM_CCORR_NORMED

  

• method=CV_TM_CCOEFF

  

  where

  

• method=CV_TM_CCOEFF_NORMED

  

• #include<opencv2\core\core.hpp>
  #include<opencv2\highgui\highgui.hpp>
  #include<opencv2\imgproc\imgproc.hpp>
  #include<iostream>
  
  using namespace std;
  using namespace cv;
  
  Mat src,tmpl,result;
  int  matchMethod = 0;
  Mat src_gray,tmpl_gray;
  
  void on_match(int,void*);
  
  int main()
  {
  	src = imread("fruits.jpg");
  	tmpl = imread("template.jpg");
  	
  	if (!src.data)
  		return-1;
  	cvtColor(src,src_gray,CV_RGB2GRAY);
  
  	if (!tmpl.data)
  		return-1;
  	cvtColor(tmpl,tmpl_gray,CV_RGB2GRAY);
  
  	namedWindow("MatchImage");
  	namedWindow("Result");
  	createTrackbar("匹配演算法","MatchImage",&matchMethod,5,on_match);
  
  	on_match(matchMethod,0);
  
  	waitKey();
  	return 0;
  
  }
  
  void on_match(int,void*)
  {
  	Mat img = src_gray.clone();
  	matchTemplate(src_gray,tmpl_gray,result,matchMethod);
  	///定位
  	double minValue,maxValue;
  	Point minLoc,maxLoc;
  	Point matchLoc;
  	minMaxLoc(result,&minValue,&maxValue,&minLoc,&maxLoc,Mat());
  
  	if( matchMethod  == CV_TM_SQDIFF || matchMethod == CV_TM_SQDIFF_NORMED )
      { matchLoc = minLoc; }
    else
      { matchLoc = maxLoc; }
  
  	rectangle(img,matchLoc,Point(matchLoc.x+tmpl.cols,matchLoc.y+tmpl.rows),Scalar::all(0),2,8,0);
  	rectangle( result, matchLoc, Point( matchLoc.x + tmpl.cols , matchLoc.y + tmpl.rows ), Scalar::all(0), 2, 8, 0 );
  
  	imshow("MatchImage",img);
  	imshow("Result",result);
  
  }