期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：6
出版社：S.S. Mishra
摘要：Image segmentation is one of the major tasks in image processing. It is the process of subdividing a digital image into its constituent parts/regions. This paper provides an overview of image segmentation methods based on the use of Particle Swarm Optimization (PSO) based clustering techniques. PSO belongs to the unsupervised classification techniques.PSO as one of the latest and emerging image segmentation techniques inspired from the nature, was developed by Dr Kenney and Dr Eberhart in 1995, and it has been widely used as an optimization tool in different applicable areas including computer graphics, biological or medical science, tele-communications, signal processing, data mining etc. The paper surveys PSO based methods to search cluster center in the arbitrary data set automatically without any input knowledge about the number of naturally occurring regions in the data, and their applications to image segmentation.
关键词：Particle Swarm Optimization (PSO); PSO Clustering; Support Vector Data Description PSO; Mixture ;Model Kernel PSO
