A PSO Based Merge Algorithm for Color Image Segmentation

Abstract

This paper proposes an improved method of image segmentation by using particle swarm optimization (PSO) based merge. The PSO algorithm is used to find optimum number of clusters which will be used as a limiting value in merge algorithm. The performance of algorithm is measured using a validity index which is measured division of intra-cluster distance whose minimum value is desired and inter-cluster distance for which a maximum value is required. Once optimum number of cluster is found then PSO clustering algorithm is again applied to generate large number of clusters, then from these large numbers of clusters, pair of clusters with most similar characteristics are merged iteratively until numbers of clusters are reduced up to optimum number of clusters. The similarity measure is taken as Davies-Bouldin Index. The proposed merge algorithm is performing better than simple PSO algorithm.