Novel fitness measure for evolutionary image matching simulation

Posted by Nick Johnson on Stack Overflow See other posts from Stack Overflow or by Nick Johnson
Published on 2009-04-30T13:56:20Z Indexed on 2010/05/17 3:20 UTC
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genetic-algorithm

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genetic-programming

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algorithm

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evolutionary-algorithm

I'm sure many people have already seen demos of using genetic algorithms to generate an image that matches a sample image. You start off with noise, and gradually it comes to resemble the target image more and more closely, until you have a more-or-less exact duplicate.

All of the examples I've seen, however, use a fairly straightforward pixel-by-pixel comparison, resulting in a fairly predictable 'fade in' of the final image. What I'm looking for is something more novel: A fitness measure that comes closer to what we see as 'similar' than the naive approach.

I don't have a specific result in mind - I'm just looking for something more 'interesting' than the default. Suggestions?

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