Artificial bee colony based image clustering

Abstract

The paper presents a novel approach of clustering image datasets with artificial bee colony (ABC) technique. From our simulations it is found that ABC is able to optimize the quality measures of clusters of image datasets. To claim the superiority of ABC based clustering we have compared the outcomes of ABC with the classical K-means and popular Particle Swarm Optimization (PSO) algorithms for the same datasets. The comparisons results reveal the suitability of ABC for image clustering in all image datasets. © 2012 Springer-Verlag GmbH Berlin Heidelberg.