Content-based image retrieval through compressed indices based on vector quantized images

Chia Hung Yeh*, Chung J. Kuo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


A multimedia database system should deal efficiently with both image compression and retrieval functions. It is critical to develop image indexing techniques that search databases based on their content in a compressed domain. We propose a new scheme, query by index image, based on vector quantization, to facilitate image retrieval in a compressed domain. The proposed algorithm exploits different index images obtained by sorting codevectors to capture various kinds of image feature. Hence, intrablock correlation and interblock correlation in an image can be efficiently represented. Our proposed algorithm not only can extract features from the pixel domain but also from a transform domain, such as that of wavelet coefficients. Experimental results demonstrate that the retrieval performance of the proposed scheme is more accurate than that of other similar methods.

Original languageEnglish
Article number017001
JournalOptical Engineering
Issue number1
Publication statusPublished - 2006 Jan
Externally publishedYes


  • CBIR
  • Image content analysis
  • Image retrieval
  • Index images
  • VQ
  • Wavelet

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • General Engineering


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