Image Thresholding with Cell-like P Systems

Abstract

P systems are a new class of distributed parallel computing models. In this paper, a novel three-level thresholding approach for image segmentation based on celllike P systems is proposed in order to improve the computational efficiency of multilevel thresholding. A cell-like P system with a specially designed membrane structure is developed and an improved evolution mechanism is integrated into the cell-like P system. Due to parallel computing ability and particular mechanism of the cell-like P system, the presented thresholding approach can effectively search the optimal thresholds for threelevel thresholding based on total fuzzy entropy. Experimental results of both qualitative and quantitative comparisons for the proposed approach and GA-based and PSO-based approaches illustrate the applicability and effectiveness.