Exploiting a growing self-organizing map for adaptive and efficient color quantization

Ping Lin Chang, Wei-Guang Teng

研究成果: Conference contribution

摘要

Studies on color quantization have indicated that its applications range from the relaxation of displaying hardware constraints in early years to a modern usage of facilitating content-based image retrieval tasks. Among many alternatives, approaches based on neural network models are generally accepted to be very effective in color quantization. However, the inefficiency prevents their usefulness from practical usage. In view of this, we thus propose to incorporate a growing quadtree structure to the self-organizing map (GQSOM) technique in this work. Specifically, the strategy of inheriting from parent neurons hierarchically facilitates a much more efficient and flexible learning process. Both theoretical and empirical studies show that our approach is adaptive in determining an appropriate number of quantized colors. Moreover, the efficiency is significantly improved without compromise of the effectiveness.

原文English
主出版物標題Advances in Multimedia Information Processing - PCM 2009 - 10th Pacific Rim Conference on Multimedia, Proceedings
頁面1219-1229
頁數11
DOIs
出版狀態Published - 2009 十二月 1
事件10th Pacific Rim Conference on Multimedia, PCM 2009 - Bangkok, Thailand
持續時間: 2009 十二月 152009 十二月 18

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5879 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Other

Other10th Pacific Rim Conference on Multimedia, PCM 2009
國家Thailand
城市Bangkok
期間09-12-1509-12-18

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • 引用此

    Chang, P. L., & Teng, W-G. (2009). Exploiting a growing self-organizing map for adaptive and efficient color quantization. 於 Advances in Multimedia Information Processing - PCM 2009 - 10th Pacific Rim Conference on Multimedia, Proceedings (頁 1219-1229). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 5879 LNCS). https://doi.org/10.1007/978-3-642-10467-1_123