关键词: 图像分割, 模糊C-均值聚类, 直方图, 加权共生矩阵, 邻域滤波

Abstract: For Fuzzy C-Means clustering with local informationand kernel metric for image segmentation algorithm time complexity too large to fit in real-time occasion required, a fast nuclear space algorithm of fuzzy local information C-means clustering segmentation is proposed. Firstly, the paper uses the space distance between pixels neighborhood pixels with information and gray variance information to construct a weighted co-occurrence matrix. Secondly it combines one-dimensional histogram with two-dimensional histogram between the pixels and neighborhood pixels constructed objective function of the new algorithm. Thirdly, to improve the algorithm of noise immunity, filter processing is done to neighborhood pixels membership when pixel classification. The experimental results show that compared with KWFLICM, the proposed algorithm has advantages of better performance and save time.

Key words: image segmentation, Fuzzy C-Means clustering, histogram, weighted symbiotic matrix, neighborhood filtering