Compressed domain image retrieval by comparing vector quantization codebooks

Gerald Schaefer

doi:10.1117/12.453018

4 January 2002 Compressed domain image retrieval by comparing vector quantization codebooks

Gerald Schaefer

Proceedings Volume 4671, Visual Communications and Image Processing 2002; (2002) https://doi.org/10.1117/12.453018
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

Image retrieval and image compression are both very active fields of research. Unfortunately, in the past they were pursued independently leading to image indexing methods being both efficient and effective but restricted to uncompressed images. In this paper we introduce an image retrieval technique that operates in the compressed domain of vector quantize images. Vector quantization (VQ) achieves compression by representing image blocks as indices into a codebook of prototype blocks. By realizing that, if images are coded with their own VQ codebook then much of the image information is contained in the codebook itself, we propose the comparison of the codebooks, based on a Modified Hausdorff distance, as a novel method for compressed domain image retrieval. Experiments, based on an image database comprising many colorful pictures show this technique to give excellent results, outperforming classical color indexing techniques.

Citation Download Citation

Gerald Schaefer "Compressed domain image retrieval by comparing vector quantization codebooks", Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); https://doi.org/10.1117/12.453018

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