Weighted semi-fuzzy C-means based on histograms

doi:10.3778/j.issn.1002-8331.2010.05.056

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (5): 184-185.DOI: 10.3778/j.issn.1002-8331.2010.05.056

• 图形、图像、模式识别 • Previous Articles Next Articles

Weighted semi-fuzzy C-means based on histograms

YANG Dao-pu，MA Qiu-he，SHI Lei，CHEN Ke

Institute of Surveying and Mapping，Information Engineering University，Zhengzhou 450052，China

Received:2008-09-22 Revised:2008-12-10 Online:2010-02-11 Published:2010-02-11
Contact: YANG Dao-pu

基于直方图加权的半模糊聚类

杨道普，马秋禾，石磊，陈科

解放军信息工程大学测绘学院，郑州 450052

通讯作者: 杨道普

Abstract

Abstract: To consider the feature of image data，this paper proposes a weighted semi-fuzzy C-means algorithm.The weight is derived from histograms of image.The method also takes in HCM’s advantage.Considering the local and the entire information，it acquires a better effect.Compared with traditional methods，the test experiment with Lena and brain image demonstrates effectiveness of the algorithm，and the experiment of processing a larger image is given to show the method is faster.

Key words: histograms, Fuzzy C-Means clustering（FCM）, Hard C-Means clustering（HCM）, semi-WFCM, Otsu, image segment

摘要： 通过分析影像数据的特点，利用直方图的统计特性，结合HCM收敛速度快的优点，提出了一种基于直方图加权的半模糊化的聚类算法，此方法结合了全局与局部信息，提高了聚类的速度，改善了聚类的效果；采用Lena和脑影像实验与传统算法作比较证明了该算法的效果更好，并对一副97 658k的影像进行处理，证明了该算法效率高。

关键词: 直方图, 模糊C-均值聚类算法（FCM）, 硬C-均值聚类算法（HCM）, 半模糊加权聚类, Otsu, 影像分割

CLC Number:

TP391

YANG Dao-pu，MA Qiu-he，SHI Lei，CHEN Ke. Weighted semi-fuzzy C-means based on histograms[J]. Computer Engineering and Applications, 2010, 46(5): 184-185.

杨道普，马秋禾，石磊，陈科. 基于直方图加权的半模糊聚类[J]. 计算机工程与应用, 2010, 46(5): 184-185.

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Weighted semi-fuzzy C-means based on histograms

基于直方图加权的半模糊聚类

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