Fuzzy c-mean Clustering Image Segmentation Algorithm Research for Sport Graphics based on Artificial Life

被引：0

作者：

Liu, Xiao ^{[1
]}

Shi, Lei ^{[1
]}

机构：

[1] Shi Jia Zhuang Univ Econ, Dept Phys, Shiiazhuang 050031, Peoples R China

来源：

INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4 | 2013年 / 263-266卷

关键词：

Artificial life; FCM; Image segmentation; sport graphics;

D O I：

10.4028/www.scientific.net/AMM.263-266.2207

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, linking with the basic principle of FCM (Fuzzy c-means clustering) algorithm, on the basis of theory research, a method of the cluster analysis of FCM based on artificial life is proposed. The artificial life approach is promising in image processing because it is inherently parallel and coincides with the self-governing biological process. Firstly, the approximate optimal solution obtained by the FCM algorithm is taken as the original value, then combined with intensity-texture-position feature space in order to produce connected regions shown in the image, the final segmentation result is achieved at last. The experiment results prove that in the view of the sport image segmentation, this algorithm provides fast segmentation with high perceptual segmentation quality.

引用

页码：2207 / 2210

页数：4

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