Efficient and effective JPEG compressed domain image retrieval

Content-based image retrieval (CBIR) has been an active research area for more than two decades. However, while almost all images are stored in compressed form, the vast majority of CBIR algorithms operate in the (uncompressed) pixel domain. This not only leads to a computational overhead for feature calculation, it can also be demonstrated that image compression has a negative effect on retrieval accuracy, especially at extreme compression rates. In this paper, we present efficient and effective CBIR techniques that operate directly in the compressed domain, hence not requiring full decompression for feature extraction. In particular, we focus on the JPEG domain since most images are compressed using JPEG. We show how CBIR features can be extracted from DCT coefficients, from differentially coded DC data, and from tuned information contained in the JPEG headers.