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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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Alexander Alekhin
2021-05-01 09:44:24 +00:00
parent 1dacea3a20 8550f7e04d
commit 170bf6d7af
18 changed files with 272 additions and 33 deletions
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modules/video/src/ecc.cpp
+20 -3
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@@ -323,17 +323,34 @@ double cv::computeECC(InputArray templateImage, InputArray inputImage, InputArra
Scalar meanTemplate, sdTemplate;
int active_pixels = inputMask.empty() ? templateImage.size().area() : countNonZero(inputMask);
int type = templateImage.type();
meanStdDev(templateImage, meanTemplate, sdTemplate, inputMask);
Mat templateImage_zeromean = Mat::zeros(templateImage.size(), templateImage.type());
subtract(templateImage, meanTemplate, templateImage_zeromean, inputMask);
Mat templateMat = templateImage.getMat();
Mat inputMat = inputImage.getMat();
/*
* For unsigned ints, when the mean is computed and subtracted, any values less than the mean
* will be set to 0 (since there are no negatives values). This impacts the norm and dot product, which
* ultimately results in an incorrect ECC. To circumvent this problem, if unsigned ints are provided,
* we convert them to a signed ints with larger resolution for the subtraction step.
*/
if(type == CV_8U || type == CV_16U) {
int newType = type == CV_8U ? CV_16S : CV_32S;
Mat templateMatConverted, inputMatConverted;
templateMat.convertTo(templateMatConverted, newType);
cv::swap(templateMat, templateMatConverted);
inputMat.convertTo(inputMatConverted, newType);
cv::swap(inputMat, inputMatConverted);
}
subtract(templateMat, meanTemplate, templateImage_zeromean, inputMask);
double templateImagenorm = std::sqrt(active_pixels*sdTemplate.val[0]*sdTemplate.val[0]);
Scalar meanInput, sdInput;
Mat inputImage_zeromean = Mat::zeros(inputImage.size(), inputImage.type());
meanStdDev(inputImage, meanInput, sdInput, inputMask);
subtract(inputImage, meanInput, inputImage_zeromean, inputMask);
subtract(inputMat, meanInput, inputImage_zeromean, inputMask);
double inputImagenorm = std::sqrt(active_pixels*sdInput.val[0]*sdInput.val[0]);
return templateImage_zeromean.dot(inputImage_zeromean)/(templateImagenorm*inputImagenorm);