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 (t(1)*, t(2)*, ... , 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.