1.模板匹配介绍
- 模板匹配就是在整个图像区域发现与给定子图像匹配的小块区域;
- 模板匹配需要首先给定一个模板图像;
- 另外需要一张待检测的图像;
- 工作方法:在待检测图像上,从左到右,从上到下计算模板图像与重叠子图像的匹配度,匹配程度越大,两者相同的可能性越大。
2.API
matchTemplate
InputArray mask=noArray()
enum cv::TemplateMatchModes {
cv::TM_SQDIFF_NORMED = 1,
minMaxLoc(src, minVal, maxVal, minLoc, maxLoc, mask)
3.实例代码
int match_method = TM_SQDIFF;
const char* INPUT_T = "input image";
const char* OUTPUT_T = "result image";
const char* match_t = "template match-demo";
void Match_Demo(int, void*);
int main(int argc, char** argv) {
src = imread("D:/vcprojects/images/flower.png");
temp = imread("D:/vcprojects/images/t2.png");
if (src.empty() || temp.empty()) {
printf("could not load image...\n");
namedWindow(INPUT_T, CV_WINDOW_AUTOSIZE);
namedWindow(OUTPUT_T, CV_WINDOW_NORMAL);
namedWindow(match_t, CV_WINDOW_AUTOSIZE);
const char* trackbar_title = "Match Algo Type:";
createTrackbar(trackbar_title, OUTPUT_T, &match_method, max_track, Match_Demo);
void Match_Demo(int, void*) {
int width = src.cols - temp.cols + 1;
int height = src.rows - temp.rows + 1;
Mat result(width, height, CV_32FC1);
matchTemplate(src, temp, result, match_method, Mat());
normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat());
minMaxLoc(result, &min, &max, &minLoc, &maxLoc, Mat());
if (match_method == TM_SQDIFF || match_method == TM_SQDIFF_NORMED) {
rectangle(dst, Rect(temLoc.x, temLoc.y, temp.cols, temp.rows), Scalar(0, 0, 255), 2, 8);
rectangle(result, Rect(temLoc.x, temLoc.y, temp.cols, temp.rows), Scalar(0, 0, 255), 2, 8);
imshow(OUTPUT_T, result);
