The JPEG still picture compression standard
Communications of the ACM - Special issue on digital multimedia systems
International Journal of Computer Vision
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
The MIR flickr retrieval evaluation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Storage and retrieval of compressed images
IEEE Transactions on Consumer Electronics
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
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While content-based image retrieval (CBIR) has been an active research area for more than two decades, the computational overhead associated with image feature extraction is often high, making existing methods unsuitable for on-line retrieval where image features need to be extracted during the retrieval process. In this paper, we present an image retrieval algorithm for JPEG images that works in an extremely fast fashion, and is based solely on information contained in the file headers. In particular, we demonstrate that optimising the Huffman tables of JPEG files not only leads to improved compression but also allows retrieval based on the (image adapted) Huffman tables. Exploiting this leads to a retrieval method that is about 40 times faster than existing compressed domain algorithms and at least 150 times faster than common pixel-domain methods. While retrieval performance on its own does not quite match that of current techniques, the method is shown to work well as an image filter to discard a large part of a database in an efficient way. Combined with a more accurate compressed-domain retrieval algorithm it is found that retrieval time can be shortened by about 80% without sacrificing retrieval accuracy.