Particle Swarm Optimization of Cellular Automata Rules for Edge Detection

Cellular automata have been widely used for solving the edge detection problem. This paper proposes an algorithm which optimizes cellular automata rules using Particle Swarm Optimization based on an existing method in the literature. Moreover, the method is extended from grayscale to colour images by performing the optimization on each colour channel individually. A discussion on choosing the proper fitness function as well as comparative results with respect to the state-of-the-art are presented. As our algorithm is comparable to the Canny and Sobel edge detectors, it could be used in image segmentation tasks as a subroutine for edge detection.