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Cellular Automata (CA) are common and most simple models of parallelcomputations. Edge detection is one of the crucial task in image processing,especially in processing biological and medical images. CA can be successfullyapplied in image processing. This paper presents a new method for edgedetection of binary images based on two dimensional twenty five neighborhoodcellular automata. The method considers only linear rules of CA for extractionof edges under null boundary condition. The performance of this approach iscompared with some existing edge detection techniques. This comparison showsthat the proposed method to be very promising for edge detection of binaryimages. All the algorithms and results used in this paper are prepared inMATLAB.

A Cellular Automata based Optimal Edge Detection Technique using Twenty-Five Neighborhood Model