Variable structure neural network for adaptive color clustering

Jun Zhang*, Jinglu Hu

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

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.

本文言語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
出版社Acta Press
ページ248-252
ページ数5
ISBN(印刷版)9780889868236
DOI
出版ステータスPublished - 2010
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月 172010 2月 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
国/地域Austria
CityInnsbruck
Period10/2/1710/2/19

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識
  • 信号処理
  • 通信

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