Image database indexing using JPEG coefficients

Abstract

Image database indexing is used for efficient retrieval of images in response to a query expressed as an example image. The query image is processed to extract information that is matched against the index to provide pointers to similar images. We present a technique that facilitates content similarity-based retrieval of jpeg-compressed images without first having to uncompress them. The technique is based on an index developed from a subset of jpeg coefficients and a similarity measure to determine the difference between the query image and the images in the database. This method offers substantial efficiency as images are processed in compressed format, information that was derived during the original compression of the images is reused, and extensive early pruning is possible. Initial experiments with the index have provided encouraging results. The system outputs a set of ranked images in the database with respect to the query using the similarity measure, and can be limited to output a specified number of matched images by changing the threshold match.