An efficient multithresholding method for image segmentation based on PSO

In the area of image processing, segmentation of an image into multiple regions is very important for classification and recognition steps. It has been widely used in many application fields such as medical image analysis to characterize and detect anatomical structures, robotics features extraction for mobile robot localization and detection and map procession for lines and legends finding. In this paper, we describe a novel method for segmentation of images based on Particle Swarm optimization for determining multilevel threshold for a given image. The proposed method is compared with other known multilevel segmentation methods to demonstrate its efficiency. Experimental results show that this method can reliably segment and give threshold values than other methods considering different measures. Keywords—Multilevel segmentation; Particle Swarm Optimization; fitness function; Image processing