The Application Of Cellular Automata And Fuzzy Cellular Automata

Cellular automata (CA) are dynamical systems in which space and time are discrete. As a discrete model to realize complex system, cellular automata had generated many interests because of its usefulness for resolving many factual problems.This paper briefly introduces the basic theory and the development of cellular automata and then we apply the classical CA model in the image processing. A new method called cellular automata edge detection model is presented to extract the edge of the image. In order to test this model, we use this model to detect three edges of images; at the same time we use an inner function of MATLAB to detect the edges of images, as a reference segmentation of this method. In our method, the evolution does not need any person participates, so our method can deal with any grayscale image. Meanwhile, it is a new attempt about the CA using on the image processing.Otherwise, we also discussed the theory of cellular automata itself and try to put fuzzy logic into the cellular automata to deal with many uncertain aspects and problems of imprecise and vague data of the real world, thereby made the ability of simulation of CA stronger and more intelligent and enrich the theory of CA. For test the fuzzy cellular model, we contrapose classical two populations' cellular automata model of biology, uncertain aspects and problems of imprecise and vague data are considered in this model. We obtain good results.