iphone opencv - 模板匹配 [英] iphone opencv - template matching
问题描述
我已经在我的iphone项目中实现了这个OpenCV版本：
i've implemented this OpenCV build into my iphone project:
http://aptogo.co.uk/2011/09/opencv-framework-for-ios/
它构建成功，我知道如何用我的相机捕获图像，灰度和显示在一个imageview。
It builds successfully and i know how to capture an image with my camera, grayscale it and show it on an imageview.
但我会喜欢做的是模板匹配与我捕获的图像（使用相机）对模板图像。
But what i'd like to do is templatematching with the image that i captured (with the camera) against an template image.
我有两个图像grayscaled，但我只是不知道'matchTemplate'工作。这是我到目前为止：
I have both images grayscaled, but i just don't get how the 'matchTemplate' works. This is what i have so far:
cv::Mat grayFrame, grayImg, output;
// This is the template image which i store in a cv::Mat and
// after that i grayscale the image
UIImage *testImage = [UIImage imageNamed:@"qr.png"];
cv::Mat tempMat = [testImage CVMat];
cv::cvtColor(tempMat, grayImg, cv::COLOR_RGB2GRAY);
// Convert captured frame to grayscale
cv::cvtColor(_lastFrame, grayFrame, cv::COLOR_RGB2GRAY);
// Having trouble here...
cv::matchTemplate(grayFrame, grayImg, output, CV_TM_CCORR_NORMED);
// Display result
// This already works for both the captured image and the template image
camView.image = [UIImage imageWithCVMat:grayFrame];
此代码的问题是这行：
cv :: matchTemplate（grayFrame，grayImg，output，1）;
cv::matchTemplate(grayFrame, grayImg, output, 1);
我不确定我是否正确。因为我不会在输出像MinMax得到结果，以获得找到的匹配的位置...我甚至传递正确的变量到matchTemplate函数... ??
I'm not sure if i'm doing it right. Because i don't get a result back in 'output' like "MinMax" to get the positions of the found match... Am i even passing the right variables to the matchTemplate function...??
无论如何，有人可以告诉我我做错了什么以及如何使这项工作？
Anyway, can someone please tell me what i'm doing wrong and how to make this work?
- edit -
添加了我的变量output的屏幕截图
感谢任何帮助！
推荐答案
matchTemplate（）函数返回一个矩阵，其值表示原始图像的每个像素上匹配的概率。它包含浮点数据并具有相同的大小（宽度/高度与输入）。要提取最可能匹配的位置，必须对结果运行minMaxLoc（）函数。
The matchTemplate() function returns a matrix whose values represent the probability of the match on every pixel of the original image. It contains floating-point data and has the same size (width/height as the input). To extract the position of the most likely match, you must run the minMaxLoc() function over the result.
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