摘要
针对模糊C均值聚类算法(FCM)聚类过程中,初始聚类中心通过随机产生、类别数的确定通过预定义的方式实现的问题,利用减法聚类(SCM)以及聚类有效性函数,实现对FCM聚类过程的聚类中心和聚类类别数自动进行设定,实现了数据的自适应聚类,并将其应用到了CT图像的自动分割中。实验结果表明,该方法是有效的。
In the traditional fuzzy C - means method （ FCM）, the initial clustering center point was defined by randomization, and clustering classes was an changeable in the method. In this paper, by using the Subtractive Clustering Method and clustering validity function, set up the clustering center point was and the clustering classes in this new method, auto - adapted clustered the data set was implemented, and applied this method to the segmentation for CT images. The result of test indicates this is an effectively method.
出处
《陕西理工学院学报（自然科学版）》
2008年第2期55-58,共4页
Journal of Shananxi University of Technology:Natural Science Edition
基金
安康学院专项科研计划资助项目(2007AKXY021)
