关键词: 模糊C均值聚类, 图像分割, 马氏距离

Abstract: Fuzzy C-Means（FCM） clustering is one of well-known unsupervised clustering techniques，which has been widely used in automated image segmentation. However，most of fuzzy partition clustering algorithms are based on Euclidean distance function which can only be used to detect spherical structural clusters，and have disadvantages in runtime. This paper presents a Mahalanobis distance-based fuzzy C-means clustering image segmentation algorithm. Experiments show that the proposed method improves the segmentation runtime on the basis of segmentation qualities. Experimental results show that the proposed method is effective.

Key words: fuzzy C-means clustering, image segmentation, Mahalanobis distance