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It was proved that genetic algorithms are the most powerful unbiased optimization techniques for sampling a large solution space. Because of unbiased stochastic sampling, they were quickly adapted in image processing. They were applied for the image enhancement, segmentation, feature extraction and classification as well as the image generation. This article gives a brief overview of the canonical genetic algorithm and it also reviews the tasks of image pre-processing. The survey of publications of this topic leads to the conclusion that the field of genetic algorithms applications is growing fast. The constant improvement of genetic algorithms will definitely help to solve various complex image processing tasks in the future.
Paulinas et al. (Fri,) studied this question.
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