Image indexing and retrieval based on vector quantization

  • Authors:
  • Shyh Wei Teng;Guojun Lu

  • Affiliations:
  • Gippsland School of Information Technology, Monash University, Gippsland Campus, Churchill, Vic. 3842, Australia;Gippsland School of Information Technology, Monash University, Gippsland Campus, Churchill, Vic. 3842, Australia

  • Venue:
  • Pattern Recognition
  • Year:
  • 2007

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Abstract

To effectively utilize information stored in a digital image library, effective image indexing and retrieval techniques are essential. This paper proposes an image indexing and retrieval technique based on the compressed image data using vector quantization (VQ). By harnessing the characteristics of VQ, the proposed technique is able to capture the spatial relationships of pixels when indexing the image. Experimental results illustrate the robustness of the proposed technique and also show that its retrieval performance is higher compared with existing color-based techniques.