Abstract
Genetic Programming can be used to evolve complex
objects. One field, where GP may be used is image
analysis. There are several works using evolutionary
methods to process, analyse or classify images. All
these procedures need an appropriate fitness function,
that is a similarity measure. However, computing such
measures usually needs a lot of computational time. To
solve this problem, the notion of efficiently
computable fitness functions was introduced, and their
theory was already examined in detail. the practical
aspects of these fitness functions are discussed.
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