Application of Particle Swarm Optimization in 2D Fuzzy Entropy Image Segmentation
A image segmentation algorithm based on particle swarm optimization and 2D fuzzy entropy is presented.In this method,2D histogram is built in terms of the message of the gray values of every pixel and its neighboring region,and 2D fuzzy entropy is regarded fitness function of particle swarm optimization algorithm,and the optimal combination of the fuzzy parameters is searched by particle swarm optimization algorithm,and the optimal threshold is determined.Experiments are conducted on real object pictures,and the results show that the approach presented herein performs better than some classical threshold selection methods do,and is a efficient image segmentation method.