Cellular automata for edge detection of images

Cellular automata are discrete dynamical systems whose function is completely specified in terms of local relation. Guided by a suitable recipe, they can simulate a whole hierarchy of structures and phenomena. In this paper, a new method called cellular automata edge detection model is presented to extract the edge of the image. In this model, the information orientation method is used to deal with the gray scale matrix of the image, a new kind of neighborhood of cellular automata is defined, and then a suitable local rule of the cellular automata is designed. Cellular automata edge detection model can extract the edge of the image without people participating in the course. Meanwhile, it is a new attempt at the cellular automata model using on the image processing.