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Image segmentation plays an important role in many image processing applications. In order to improve the color image segmentation effect, better represent the image information, use the complex network theory to research the color image segmentation, analyze the image from the perspective of the network community structure model and propose a clearer method of color image segmentation expression. According to the similarities between pixels in color image, the image of network structure is constructed and the image data is modeled. Then the cluster classification algorithm is used to conduct community detection of the good network community structure, Clustering of similar pixels in the image and finally the result of image segmentation. Different color images are randomly selected from the BSDS300 image database for experiments. The results of the analysis of the image segmentation results show that the proposed algorithm is superior to the traditional color image segmentation algorithm in accuracy, and can achieve better segmentation results. At the same time, Community segmentation algorithm for color image segmentation feasibility and effectiveness.