I'm trying to find the best algorithm for my task. I have images looking like this one:
I want to find the most similar ones from a set of such images. I tried several algorithms to compute the similarity value (sift - opencv2, structural similarities - skimage.measure.compare_ssim, pixel similarity, wasserstein_distance...). None of them seems to work as I'd like to. For example sift returned almost maximal similarity for the above image and this one:
Which is far from perfect. Are there any algorithms which could perform better on such a task?