模板匹配失在一幅图中寻找与另一幅模板图最匹配的部分的技术。模板匹配不是基于直方图的，而是在通过输入图像上进行滑动，对实际的图像块和输入图像进行匹配的方法。模板匹配由MatchTemplate()函数完成，其匹配模式有以下六种：
模板匹配示例：
#include"stdafx.h" #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp> #include <opencv2/core/core.hpp> #include <opencv2/objdetect/objdetect.hpp> #include<opencv2/photo/photo.hpp> #include <string> #include <vector> #include <iostream> using namespace cv; using namespace std; #define WINDOW_NAME1 "【原始图片】" #define WINDOW_NAME2 "【效果窗口】" Mat g_srcImage, g_templateImage, g_resultImage; int g_nMatchMethod; int g_nMaxTrackbarNum = 5; void on_Matching(int, void*); int main() { system("color 2F"); //分别载入原图像和模板快 g_srcImage = imread("E:\\pictures\\For_Project\\New_opencv\\liu.jpg",1); g_templateImage = imread("E:\\pictures\\For_Project\\New_opencv\\liuface.jpg",1); namedWindow(WINDOW_NAME1, CV_WINDOW_AUTOSIZE); namedWindow(WINDOW_NAME2, CV_WINDOW_AUTOSIZE); //创建滑动条并进行初始化 createTrackbar("方法", WINDOW_NAME1, &g_nMatchMethod, g_nMaxTrackbarNum, on_Matching); on_Matching(0, 0); while((char)waitKey(0)!='q'){} return 0; } void on_Matching(int, void*) { //给局部变量初始化 Mat srcImage; g_srcImage.copyTo(srcImage); //初始化用于结果的输出矩阵 int resultImage_cols = g_srcImage.cols - g_templateImage.cols + 1; int resultImage_rows = g_srcImage.rows - g_templateImage.rows + 1; g_resultImage.create(resultImage_cols, resultImage_rows, CV_32FC1); //进行匹配和标准化 matchTemplate(g_srcImage, g_templateImage, g_resultImage, g_nMatchMethod); normalize(g_resultImage, g_resultImage, 0, 1, NORM_MINMAX, -1, Mat()); double minValue, maxValue; Point minLocation, maxLocation; Point matchLocation; //通过minMaxLoc定位最匹配部位 minMaxLoc(g_resultImage, &minValue, &maxValue, &minLocation, &maxLocation, Mat()); if (g_nMatchMethod == TM_SQDIFF || g_nMatchMethod == CV_TM_SQDIFF_NORMED) { matchLocation = minLocation; } else { matchLocation = maxLocation; } //绘制匹配结果并输出 rectangle(srcImage, matchLocation, Point(matchLocation.x + g_templateImage.cols, matchLocation.y + g_templateImage.rows), Scalar(0, 0, 255), 2, 8, 0); rectangle(g_resultImage, matchLocation, Point(matchLocation.x + g_templateImage.cols, matchLocation.y + g_templateImage.rows), Scalar(0, 0, 255), 2, 8, 0); imshow(WINDOW_NAME1, srcImage); imshow(WINDOW_NAME2, g_resultImage); }
从中看出除了方法2 (TM_CCORR)得到错误的匹配结果外，其余的5种都相对准确。
