Histogram based Evolutionary Dynamic Image Segmentation

This paper describes an evolutionary approach for unsupervised gray-scale image segmentation that segments an image into its constituent parts automatically. The aim of this algorithm is to produce precise segmentation of images using intensity information along with neighborhood relationships. The proposed technique automatically determines the number of clusters. The proposed algorithm is evaluated on well known natural images and its performance is compared to that of DCPSO, MAMA based segmentation techniques etc. The proposed algorithm is very simple in implementation. Experimental results shown that the algorithm generates good quality segmented image. KeywordsClustering; Segmentation; Thresholding; Histogram Analysis; Genetic Algorithm.