By means of analyzing kernel clustering algorithm and rough set theory, a novel clustering algorithm, rough kernel k-means clustering algorithm, was proposed for clustering analysis.

通过研究核聚类算法，以及粗糙集，提出了一个新的用于聚类分析的粗糙核聚类方法。

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And this paper also improved the initial center point's selection of K-Means clustering algorithm.

另对聚类算法初始聚类中心的选取也做了改进。

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According to the characters of the images, the algorithm separated image into several regions by K-means clustering algorithm, and each region is equalized respectively within their gray levels.

该算法基于图像的特点，利用K均值聚类算法将图像分成几个灰度区间，然后再分别进行均衡化。

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