Fuzzy Evolutionary Programming for Image Processing
نویسنده
چکیده
The method of evolutionary programming is used to search for the optimal solution in fuzzy clustering of images and in fuzzy boundary detection. In fuzzy evolutionary clustering, the Gibb's probability distribution is employed to model the evolution of object clusters, and the total fuzzy distance is used as a measurement of fitness. In image boundary detection, both geometrical shape and arbitrary images are studied. The Hough transform algorithms are fuzzified to monitor the fitness of the fuzzy boundaries, and evolutionary programming is applied to attain the best match. Experiments show the methods are remarkably effective.
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