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by osrec
3234 days ago
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Very impressive indeed. I was wondering, how did you determine your criteria for matching (i.e. the hash distance at which two triangles are considered different)? Also, could this be extended to colour transformations as well (perhaps by using a wavelet transform to extract phase for comparison, rather than amplitude)? |
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Yeah, the query image is broken into a number of fragments and then the hash of each fragment/triangle is checked against the hashes stored in the database using a nearest neighbor search (well you find any neighbors within a certain distance/threshold, I found a hamming distance of 8 to be a pretty good threshold).
Currently only one fragment of the query image needs to match a database image for the images to be considered a match. You could also put some threshold on the number of fragments that need to match but this is only a proof of concept I haven't had time to find the perfect combination yet.
>could this be extended to colour transformations
Yeah, actually after you have re-transformed the triangles to be equilateral you can apply a lot of other techniques to future improve the search. You can even use NON-affine transformation partial image matching on the triangles to match fragments that only partially match fragments stored in the database.