Multi-level Threshold Image Segmentation Using Artificial Bee Colony Algorithm

Image segmentation is still a crucial problem in image processing. In this paper, we proposed a novel multi-level image segmentation method based on PSNR using artificial bee colony algorithm (ABCA). PSNR is considered as an objective function of ABCA. The best multi-level thresholds (t₁*,t₂*,...,t_n-1*,t_n*) are those which can make the PSNR maximize. Further, we compare entropy and PSNR in segmenting gray-level images and noisy images. Through experiments, it is found that the entropy isn´t suitable to be applied to segmentation of images with Gaussian noise. So we can conclude that entropy can´t be used for noisy image segmentation. The experiments results demonstrate our proposed method is effective and efficient.