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Pattern recognition has provoked a great interest in the last decades. As a consequence, numerous engineering applications have been developed, such as medicai diagnosis aiding, automatic signal analysis, industrial inspection, automatic monitoring systems, automatic digital information searching, etc. The complexity of a pattern recognition system is high because real patterns present in fornis of large extent of varieties, suffering from linear transformations even nonlinear deformations. The objective of this work is to develop a evolutive cellular system for rotational invariant pattern recognition based on the fundamental mechanism of cellular automata, which has been successfully used to model and simulate complex problems. The proposed model extracts efficiently global features invariant to pattern rotation by local interactions among cellulars.

Sistema celular evolutivo para reconhecimento de padrão invariante