Compressed domain image retrieval by comparing vector quantization codebooks

Image retrieval and image compression are both very active elds of research. Unfortunately, in the past they were pursued independently leading to image indexing methods being both eÆcient and e ective but restricted to uncompressed images. In this paper we introduce an image retrieval technique that operates in the compressed domain of vector quantised images. Vector quantization (VQ) achieves compression by representing image blocks as indices into a codebook of prototype blocks. By realising 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 Modi ed Hausdor distance, as a novel method for compressed domain image retrieval. Experiments, based on an image database comprising many colourful pictures show this technique to give excellent results, outperforming classical colour indexing techniques.