Using Fuzzy c-Means Cluster for Histogram-Based Color Image Segmentation

被引：9
|
作者：
Huang, Zhi-Kai [1 ]
Xie, Yun-Ming [1 ]
Liu, De-Hui [1 ]
Hou, Ling-Ying [1 ]
机构：
[1] Nanchang Inst Technol, Dept Machinery & Dynam Engn, Nanchang 330099, Jiangxi, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND COMPUTER SCIENCE, VOL 1, PROCEEDINGS | 2009年
关键词：
Histogram; FCM; Image segmentation; ENTROPY;
D O I：
10.1109/ITCS.2009.130
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we proposed a fuzzy c-means (FCM) cluster based adaptive thresholding segmentation algorithm for color image. The main advantage of this method is that, it does not require a priori knowledge about number of objects in the image. It calculates the threshold values automatically with the help of merging process. The first step of the method is that construct the histograms for each color channel. With this aim, information based histogram of the color intensities have been obtained. In the second step of the method, Fuzzy 2-partition is used on each of the three histograms in R(red), G(green) and B(blue) dimensions, color image segmentation is obtained the performance of the FCM cluster for each color channel. Experiment results show that this method can determine automatically the number of the thresholds levels and achieves good results for color images.
引用
收藏
页码：597 / 600
页数：4
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