Multilevel Renyi’s Entropy Threshold Selection Based on Bacterial Foraging Algorithm

Abstract

A novel stochastic optimization approach to solve multilevel thresholding problem in image segmentation using bacterial foraging (BF) technique is presented. The BF algorithm is based on the foraging behavior of E. Coli bacteria which is present in the human intestine. The proposed BF algorithm is used to maximize Renyi’s entropy function. The utility of the proposed algorithm is aptly demonstrated by considering several benchmark test images and the results are compared with those obtained from particle swarm optimization (PSO) and genetic algorithm (GA) based methods. The experimental results show that the proposed algorithm could demonstrate enhanced performance in comparison with PSO and GA in terms of solution quality and stability. The computation speed is accelerated and the quality improved through the use of this strategy.