Variable structure neural network for adaptive color clustering

Jun Zhang, Jinglu Hu

研究成果: Conference contribution

抜粋

Color clustering is widely used for color image segmentation, transmission and visualization. However, traditional clustering algorithms have difficulty in adaptive determination of the proper cluster number. In this paper, a variable structure self-organizing map neural network (VSSOM) is proposed to achieve adaptive color clustering. It can provide the suitable cluster number and the palette for generating the clustered color image. The characteristic of the algorithm is that the output neuron of VSSOM is changed from 2 to N based on the defined learning rules during training. When the network converges, its N is the number of color clusters and the palette of clustered image is corresponding to the weights of the network. Experimental results show that the proposed algorithm has the desired ability for color clustering.

元の言語English
ホスト出版物のタイトルProceedings of the 7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications, SPPRA 2010
出版者Acta Press
ページ248-252
ページ数5
ISBN(印刷物)9780889868236
DOI
出版物ステータスPublished - 2010 1 1
イベント7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications, SPPRA 2010 - Innsbruck, Austria
継続期間: 2010 2 172010 2 19

出版物シリーズ

名前Proceedings of the 7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications, SPPRA 2010

Conference

Conference7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications, SPPRA 2010
Austria
Innsbruck
期間10/2/1710/2/19

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Communication

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  • これを引用

    Zhang, J., & Hu, J. (2010). Variable structure neural network for adaptive color clustering. : Proceedings of the 7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications, SPPRA 2010 (pp. 248-252). (Proceedings of the 7th IASTED International Conference on Signal Processing, Pattern Recognition and Applications, SPPRA 2010). Acta Press. https://doi.org/10.2316/p.2010.678-083