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中文摘要：
针对传统的模糊C-均值算法在图像分割中存在的缺陷,提出了一种基于点密度函数加权的模糊C-均值聚类算法。将图像像素的点密度函数作为权值,并依据类间相关度定义了一个聚类有效性函数用以确定最佳聚类数,结合聚类有效性完成对图像的分割。理论分析和对比试验表明,该算法在一定程度上克服了模糊均值算法的缺陷,在图像分割中具有良好的分类精度。
英文摘要：
For the defects of traditional fuzzy C-means algorithm in image segmentation, a weighted fuzzy C-means clustering algorithm based on dot density function are proposed. Takes the dot density function of image pixels as the weight, and on the basis of inter-class correlation defines a cluster validity function to determine the optimal number of clusters and combines with cluster validity to complete the effective image segmentation. Theoretical analysis and com- parative experiments show that the algorithm overcomes the shortcomings of fuzzy means algorithm to some extent and has good classification accuracy in image segmentation.
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