Exploring content-based image indexing techniques in the compressed domain

A method is proposed for performing clustering and offline indexing on the signal representations of compressed JPEG images. The current system clusters on discrete cosine transform (DCT) blocks of JPEG images using the potential function clustering algorithm, storing indices of varying length for a posteriori comparison and processing of query images. Results presented indicate the appropriateness of using clusters derived from JPEG DCT blocks for content-based indexing. In particular, we are able to provide image summaries based on index features defined from a reference texture database, which significantly speeds the search process.