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We have a for fun project which require us to compare two black and white bitmaps of two signature and say whether they are the same persons signature. As this is just two loaded bitmaps rather than data captured from a tablet the approach is going to be a little different to normal signature recognition.

I am thinking it would require the following steps

  • Crop the bitmaps to just the signature
  • Try to work out some kind of rotation to align them
  • Resize to make the cropped / rotated bitmaps the same
  • Analyse the signature inside (maybe by breaking down into a grid)

Does anyone have any thoughts on this project? How to best do the rotation, comparison etc? Seen anything similar?

A: 

You may want to look at:SOMs for interesting pics (:D) as well as an example of how to compare image similarities.

There are two main types of Neural Networks - supervise and unsupervised. SOMs are unsupervised. Depending on your situation, you might want to take a look at supervised Neural Networks NNs are common, and quite straightforward to implement for the most part.

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