Multilevel minimum cross entropy threshold selection based on the honey bee mating optimization

Image entropy thresholding approach has drawn the attentions in image segmatation. The endeavor of this paper is focused on multilevel thresholding using the minimum cross enrtop criterion. In the literature, the particle swarm optimization (PSO) had been applied to conducting the thresold selection. The adopted algorithm used in this paper is the honey bee mating optimization (HBMO). In experimnats, the two different methods are implemented for comparison with the results of segmantation. Compared to the results of PSO, the threshold selection of HBMO is more close to the optimal ones examined by the exhaustive search method. Furthermore, the segmentation result of HBMO is superior to PSO method, but it still slower than ones of PSO. Key-Words: Image segmentation, Image thresholding, Cross entropy, Particle swarm optimization, Honey bee mating optimization