Rule-based automatic segmentation of color images

Abstract

A rule-based segmentation algorithm for color images has been presented in this paper. The proposed strategy is similar to region growing algorithm where the seed points are automatically selected and grown. The similarity percents of neighboring pixels are calculated by means of fuzzy reasoning rules, and the merging of the pixels with regions is performed by comparing the similarity percent with the similarity threshold value. The algorithm does not require any prior knowledge of the number of regions existing in the image and decreases the computational load required for the fuzzy c-means (FCM). Several computer simulations have been performed and the results have been discussed. The simulation results indicate that the proposed algorithm yields segmented color image of perfect accuracy.