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As a hobbiest stamp collector, I often run into the need for classifying stamps based on minute differences, such as these:

varieties of the 1 pence Machin; courtesy of the Deegam catalogue

Now, I literally have thousands of them (in ziploc bags) and I am planning on building an automation platform, that makes a picture and immediately classifies the stamp as one of these varieties. (I make this type of integrated systems for work, so doing it at home is very feasible.)

What I am stuck at, is at identifying what type of image recognition / AI / classical fitting problem this is. It is somewhat made difficult, by the fact that the overall variation between stamps is quite large: cancels can obscure part of the image, there might be damage, color varieties, etc.

This is a representative image of what an algorithm would have to deal with:

enter image description here

I can imagine it to be a step wise approach:

  1. Normalization: crop, rotate and scale the stamp
  2. The hardest part, where any help is appreciated!
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