如何衡量 opencv 模板匹配算法的成功与否？
我了解 minmaxLoc 函数可用于查找最佳匹配的位置。但它是否也说明了这场比赛的实际表现如何？（如果是，您将如何发现？）
是否有更合适的函数来测量找到的匹配（绿色矩形）和原始模板之间的相关性？例如，如果模板图像与匹配图像中的图像相比略微旋转或平移怎么办？
我是简单地取所有 minmax-locations 的平均值还是你有什么建议？
cv::Mat cv_in_image = [in_image CVMat];
cv::Mat cv_in_template = [in_template CVMat];
cv::Mat output;
// Do some OpenCV stuff with the image
/// Create the result matrix
int result_cols = in_image.size.width - in_template.size.width + 1;
int result_rows = in_image.size.height - in_template.size.height + 1;
output.create(result_rows, result_cols, CV_32FC1);
cv::matchTemplate(cv_in_image, cv_in_template, output, cv::TM_CCORR_NORMED);
cv::normalize(output, output, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
/// Localizing the best match with minMaxLoc
double minVal; double maxVal;
cv::Point minLoc; cv::Point maxLoc;
cv::Point matchLoc;
cv::minMaxLoc(output, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat());
/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
int match_method;
if(match_method == cv::TM_SQDIFF || match_method == cv::TM_SQDIFF_NORMED) {
matchLoc = minLoc;
NSLog(@"Correlation minVal = %f", minVal);
NSLog(@"(Correlation maxVal = %f)", maxVal);
}
else {
matchLoc = maxLoc;
NSLog(@"Correlation maxVal = %f", maxVal);
NSLog(@"(Correlation minVal = %f)", minVal);
}
/// Show me what you got
cv::Rect rect1;
rect1.x = matchLoc.x;
rect1.y = matchLoc.y;
rect1.width = cv_in_template.cols;
rect1.height = cv_in_template.rows;
cv::rectangle(cv_in_image, rect1, cv::Scalar::all(0), 2, 8, 0);