Exploiting image indexing techniques in DCT domain

This paper is concerned with the indexing and retrieval of images based on features extracted directly from the JPEG discrete cosine transform (DCT) domain. We examine possible ways of manipulating DCT coefficients by standard image analysis approaches to describe image shape, texture, and color. Through the Mandala transformation, our approach groups a subset of DCT coefficients to form ten blocks. Each block represents a particular frequency content of the original image. Two blocks are used to model rough object shape; nine blocks to describe subband properties; and one block to compute color distribution. As a result, the amount of data used for processing and analysis is significantly reduced. This can lead to simple yet efficient ways of indexing and retrieval in a large-scale image database. Experimental results show that our proposed approach offers superior indexing speed without significantly sacrificing the retrieval accuracy.