Adaptive Edge Detection via Image Statistic Features and Hybrid Model of Fuzzy Cellular Automata and Cellular Learning Automata

In this paper a new approach for adaptive edge detection via image statistic features and hybrid model of fuzzy cellular automata and cellular learning automata is presented. Edge detection in image is one of the basic and most significant operations in image processing that edge detection have a lot of application in image processing. Presented method in first stage used of statistic feature of its image for primary edge detection, that cause adaptively for this method at all internal image. At the second stage fuzzy cellular automata and cellular learning automata are used for edges amplify and castrate these aren't edge. The result obtained from implementation shows That the performance of this method is much better compared to other edge detection methods.