模糊聚类算法是近年来图像分割技术领域的研究热点之一。在对模糊C均值聚类算法分析的基础上,结合目前在图像分割中的应用研究,对模糊C均值聚类算法的测度方式进行了比较分析,从单分辨率、多分辨率以及与其他算法结合3个方面,评述改进的模糊C均值聚类算法优缺点。最后,讨论模糊C均值聚类算法目前存在的问题及未来发展方向。

The fuzzy c-means (FCM) clustering algorithm for image segmentation is one of the striking research fields in recent decades.Based on the analysis of the FCM algorithm,we combine the current application research in image segmentation,and we analyze and compare it in terms of measuring the expressions of the FCM algorithm.In this paper,through three aspects,such as single-resolution,multi-resolution,and the integration of other algorithms,the advantages and disadvantages of the improved FCM algorithms are expounded.In the end,some challenges and possible trends are discussed.