A new image segmentation algorithm based on modified seeded region growing and particle swarm optimization

Abstract

Image Segmentation, a basic technique for many real world applications, has been considered in this paper. The Seeded Region Growing (SRG) algorithm, as the first and probably the simplest region growing algorithm, faces three important problems: the position of seeds, the number of seeds, and region growing strategy. Two new versions of SRG are introduced here to solve the multi seeded region growing problem, and also region growing strategy. Then Particle Swarm Optimization is utilized to solve the localization problem. Experimental results show that the proposed method is successfully applied to gray scale image segmentation.