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文章基本信息

  • 标题:Image Segmentation with Fuzzy Clustering Based on Generalized Entropy
  • 本地全文:下载
  • 作者:Li, Kai ; Guo, Zhixin
  • 期刊名称:Journal of Computers
  • 印刷版ISSN:1796-203X
  • 出版年度:2014
  • 卷号:9
  • 期号:7
  • 页码:1678-1683
  • DOI:10.4304/jcp.9.7.1678-1683
  • 语种:English
  • 出版社:Academy Publisher
  • 摘要:Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to improve anti-noise characteristic of algorithm, a window is introduced. In experiments, some commonly used images are selected to verify performance of algorithm presented. Experimental results show that the image segmentation of fuzzy clustering based on generalized entropy using neural network performs better compared to FCM and BCFCM_S1.
  • 关键词:image segmentation;spatial information;generalized entropy;neural network
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