关键词: 小生境粒子群优化算法, 最大类间方差法, 图像分割

Abstract: To determine the optimal thresholds in image segmentation，a new method based on niching particle swarm optimization is proposed in this paper.By the method of dividing niches，niching particle swarm optimization has kept the diversity of species，overcome the drawback of basic PSO，such as being subject to falling into local optimization and having the poor convergence speed，and so improved the ability of seeking global optima.The method uses maximum between-class variance（MV） technique，by the optimization of the niching particle swarm optimization object function，the optimal thresholds can be gotten，and the image by use of the thresholds can be segmented.Experimental results show that compared to maximum between-class variance technique，MV based the basic PSO algorithm，the proposed method can not only obtain ideal segmentation results，but also improve the speed greatly.

Key words: niching particle swarm optimization, Otsu, image segmentation