Being in the middle of my third week of research. I finally found the grand father of papers on the topic of image comparison and pattern recognition; “Visual Pattern Recognition by Moment Invariants” by Hu Ming-Kuei from 1962.
In this paper he makes mathematical proofs for and explains how his 7 invariants works. They are usually used for pattern recognition independent of rotation, translation, mirroring and skewing. Pretty much every paper on the topic refers back to his paper. It seems to be a cornerstone, and while I haven’t fully grasped how to use it and how to combine it with other things, what seems to be a strong solution for my problem is to combine his invariants with fourier transformations.
If things works out as planned I have a working solution both for comparison and searching. End of week I will probably write some more details about everything and some sort of conclusion of my research. I will write about my solution and explain how it works a bit then.