期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：8
页码：319-328
出版社：SERSC
摘要：Fuzzy c-means clustering (FCM) with spatial information (FCM_S) is an effective algorithm for image segmentation. However, the FCM_S algorithm is not used for color image segmentation and also it produces over-segmentation results. In this paper, we present a novel fuzzy c-means algorithm named nFCM_S that incorporates spatial information into the membership function and cluster center function for segmentation of color images. Firstly, HSV color space is used for decomposition of color images. Then, to label the data points reliably, a linearly-weighted sum image is calculated on each HSV component before clustering process. Finally, spatial information is incorporated in the standard FCM algorithm and nFCM_S is applied separately on each component of HSV color space. Experiment results have shown that the nFCM_S algorithm achieves competitive segmentation results compared to other FCM-based algorithms.
关键词：Fuzzy c-means; over-segmentation; spatial information; image ;segmentation; HSV color space
