OpenCV——模板匹配

minMaxLoc函数：

void minMaxLoc( const Mat& src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0, const Mat& mask=Mat() );

说明:

1 minMaxLoc寻找矩阵(一维数组当作向量,用Mat定义) 中最小值和最大值的位置.
2 参数若不需要,则置为NULL或者0,即可.

3 minMaxLoc针对Mat和MatND的重载中 ,第5个参数是可选的(optional),不使用不传递即可.

 //对视频进行模板匹配操作
 #include <opencv2/opencv.hpp>
 #include <iostream>

 #define MATCHMETHOD TM_CCOEFF_NORMED//宏定义匹配模式
 using namespace cv;
 using namespace std;

 Mat src,resultImage;

 int main(int argc, char** argv)
 {
     VideoCapture capture("F:/2019视觉培训内容/2019视觉培训内容/4buff1.avi");
     Mat digita_l=imread("F:/2019视觉培训内容/2019视觉培训内容/数字识别数据集/数码管/1.png");
     while (capture.read(src)) {
         Mat frame;
         src.copyTo(frame);

         //初始化输出矩阵
         int resultImage_cols = src.cols - digita_l.cols + ;
         int resultImage_rows = src.rows - digita_l.rows + ;
         resultImage.create(resultImage_cols,resultImage_rows,CV_32FC1);

         //进行匹配和标准化
         matchTemplate(src, digita_l, resultImage, MATCHMETHOD);//滑动模板，将匹配程度依此放在resultImage中
         normalize(resultImage, resultImage, , , NORM_MINMAX, -, Mat());

         //定位最匹配位置
         double minValue, maxValue;
         Point minLocation, maxLocation, matchLocation;
         minMaxLoc(resultImage,&minValue,&maxValue,&minLocation,&maxLocation,Mat());

         if(MATCHMETHOD== TM_SQDIFF|| MATCHMETHOD==TM_SQDIFF_NORMED)//这两种方法，值越小匹配读越高
         {
             matchLocation = minLocation;
         }
         else { matchLocation = maxLocation; }

         rectangle(frame, matchLocation, Point(matchLocation.x + digita_l.cols, matchLocation.y + digita_l.rows), Scalar(, , ), , , );

         imshow("匹配结果", frame);
         imshow("结果图", resultImage);

         char c = waitKey();//延时100ms
         if (c == ) //等待“Esc”
         {
             break;
         }
     }
     capture.release();//释放视频的内存
     waitKey();

     return ;
 }