Selection of Optimum Rule Set of Two Dimensional Cellular Automata for Some Morphological Operations

Abstract

The cellular automaton paradigm is very appealing and its inherent simplicity belies its potential complexity. Two dimensional cellular automata are significantly applying to image processing operations. This paper describes the application of cellular automata (CA) to various morphological operations such as thinning and thickening of binary images. The description about the selection of the optimum rule set of two dimensions cellular automata for thinning and thickening of binary images is illustrated by this paper. The selection of the optimum rule set from large search space has been performed on the basis of sequential floating forward search method. The misclassification error between the images obtained by the standard function and the one obtained by cellular automata rule is used as the fitness function. The proposed method is also compared with some standard methods and found suitable for the purpose of morphological operations.