A hierarchical clustering method for color quantization

Jun Zhang, Jinglu Hu

研究成果: Conference contribution

抄録

In this paper, we propose a hierarchical frequency sensitive competitive learning (HFSCL) method to achieve color quantization (CQ). In HFSCL, the appropriate number of quantized colors and the palette can be obtained by an adaptive procedure following a binary tree structure with nodes and layers. Starting from the root node that contains all colors in an image until all nodes are examined by split conditions, a binary tree will be generated. In each node of the tree, a frequency sensitive competitive learning (FSCL) network is used to achieve two-way division. To avoid over-split, merging condition is defined to merge the clusters that are close enough to each other at each layer. Experimental results show that HFSCL has the desired ability for CQ.

本文言語English
ホスト出版物のタイトルProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
ページ786-789
ページ数4
DOI
出版ステータスPublished - 2010
イベント2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
継続期間: 2010 8 232010 8 26

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
ISSN(印刷版)1051-4651

Other

Other2010 20th International Conference on Pattern Recognition, ICPR 2010
CountryTurkey
CityIstanbul
Period10/8/2310/8/26

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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