关键词: 图像分割, 粗糙集, 近似集, 粒计算, 粒子群

Abstract: Image segmentation method based on the classical rough set theory is lacking of accurate classification on the uncertainty of target image edge boundaries, and classical rough set information system which is built for an image with a priori granularity does not reflect the roughness information between different particle size objectives accurately. Based on the theory of approximation set of rough set model, this paper adopts an adaptive optimal graining method on the rough set representation of the image, and then builds the upper and lower approximation sets of the target and background images. According to the approximate set ideas, this paper accurately describes the edge boundaries of the target set, and improves the efficiency of the rough set approximation set maximum rough entropy combined with particle swarm algorithm at the same time, finally obtains the optimal segmentation threshold. The experimental results show that this method is feasible and effective.

Key words: image segmentation, rough set, approximation set, granular computing, particle swarm