Image Segmentation Based on Particle Swarm Optimization Technique

Abstract

Digital Image segmentation is one of the major tasks in digital image processing. It is the process of subdividing a digital image into its constituent objects. This paper gives an overview of image segmentation techniques based on Particle Swarm Optimization (PSO) based clustering techniques. PSO is one of the latest and emerging digital image segmentation techniques inspired from the nature. It was developed by Dr Kenney and Dr Eberhart in 1995, and it has been widely used as an optimization tool in areas including tele-communications , computer graphics, biological or medical science, signal processing, data mining, robotics, neural networks etc. The paper study 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.