关键词: Lab颜色空间, NBS距离, 密度峰聚类, 图像分割

Abstract: Color image segmentation is the key technology of tufted carpet digital manufacturing. The quality of image segmentation directly affects the subsequent image processing. In order to solve the problem of carpet color image segmentation, a color image segmentation algorithm based on density peak clustering and color quantization is proposed to overcome the inhomogeneous perception of human eyes in RGB color space. Firstly, color quantization is performed based on Lab color space, and then NBS distance is used to measure the difference of color perception in HVC color space. Finally, density peak clustering algorithm is used to automatically determine the clustering center and segment the carpet image. Experimental results show that the algorithm can get carpet segmentation images with few color categories and clear edges without affecting human perception.

Key words: Lab color space, NBS distance, density peak clustering, image segmentation