1 | initial version |
You can use the output-mask of findHomography (if you use RANSAC or LMEDS). Afaik the output-mask gives you a mask of inliers/outliers, so count the number of inliers and if they are high enough -> accept otherwise reject the image.
If this ain't working good enough, maybe because you have many differences in the number of inliers than you need to try to add some other verification steps (I assume you're using a feature-matching approach):
cv::KeyPointsFilter::retainBest()
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