Visual image retrieval on compressed domain with Q-distance

This paper proposes a new image retrieval scheme that works directly on compressed image (JPEG) databases. As we know, a large percentage of the image databases are stored in compressed image format, such as JPEG format. In addition, about half of the images on the Internet are also in JPEG format. Thus, image retrieval systems that require JPEG decompression greatly limit the speed of image searching. Subsequently, new methodologies for retrieving of images without JPEG decoding is needed for Web image search and compressed image database retrieval. We propose a new metric, Q-distance, that can be utilized to measure the distance between two compressed images. A system that uses Q-distance for fast image retrieval is also presented. Experiment results show that Q-distance is robust against variation and this new retrieval scheme, which directly works in the compressed image domain, is fast to execute and suitable for Web image searching and retrieval