Image segmentation by multi-level thresholding based on fuzzy entropy and genetic algorithm in cloud

In this paper, we describe a new soft computing method for segmentation of both gray level and color images by using a fuzzy entropy based criteria (cost function), the genetic algorithm, and the evolutionary computation techniques. The presented method allow us to find optimized set of parameters for a predefined cost function. Particularly, we found the optimum set of membership functions by maximizing the fuzzy entropy and based on the membership functions. Experimental results show that the offered method can reliably segment and give better threshold then Otsu Multi-Level thresholding.