Using fuzzy competitive Hopfield neural network for image segmentation

被引：0

作者：

Zhang, Xingming ^{[1
]}

Li, Fengsen ^{[1
]}

机构：

[1] Inst of Computing Technology, Chinese Acad of Sciences, Beijing, China

来源：

Ruan Jian Xue Bao/Journal of Software | 2000年 / 11卷 / 07期

关键词：

Color image processing - Computer vision - Fuzzy sets - Learning algorithms - Neural networks;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Based on the defect of self-organizing learning method, a fuzzy competitive learning method is proposed, and a fuzzy competitive Hopfield neural network for color image segmentation is designed. the fuzzy clustering on gray feature set can be realized by means of mapping image space into gray feature space, then the color image segmentation can be done. The experiment results indicate that the algorithm is of better effect and adaptive ability to noise than Ostu method for binary segmentation, and shows higher processing speed than FCM (fuzzy C mean) algorithms for multi-class segmentation.

引用

页码：953 / 956

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