Watershed image segmentation algorithm base on particle swarm and region growing

Abstract

An improved watershed image segmentation algorithm is proposed to solve the problems of noise-sensitivity and over-segmentation. The new algorithm which combined region growing with classical watershed algorithm is established by constructing an objective function, the parameter of region growing is ensured based on Shannon entropy. The particle swarm optimization algorithm is employed to search global optimization of the objective function. Experimental results show that the new watershed image segmentation algorithm can solve effectively the problem of over-segmentation and turns out to be an efficient, accurate and applied image segmentation algorithm.