Now I have extracted the two ROI,
but their relative positions do not coincide, and because it is real-time processing, there may be rotated and scaled
can not be directly obtained by subtraction of their different places.
How to find different areas (7) of the two images?
I'd suggest warping images to the common coordinate system and then subtract warped results. You could detect 2D feature points with any 2D feature detector, for example, Harris corners, or BRISK, or SIFT, then calculate a homography matrix and then use it to transform one of images to the coordinate system of another.
Also, it would be useful to apply some filtering and morphology to make robust comparisons.
I've never used Hu moments in my practice, however, Wikipedia says that they are weighted averages of image pixels. So, for each moment, you supply an image to a function and it returns you a single value, depending on all image pixels. Therefore, probably, they can detect that pictures differ, while you seem to be interested in locations of those differences. Answering this your question - unlikely.
Asked: 2015-04-21 07:31:12 -0600
Seen: 384 times
Last updated: Apr 22 '15
