The JPEG still picture compression standard
Communications of the ACM - Special issue on digital multimedia systems
International Journal of Computer Vision
Exploiting the JPEG Compression Scheme for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Image retrieval based on energy histograms of the low frequency DCT coefficients
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Features for image retrieval: an experimental comparison
Information Retrieval
Lire: lucene image retrieval: an extensible java CBIR library
MM '08 Proceedings of the 16th ACM international conference on Multimedia
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
DC stream based JPEG compressed domain image retrieval
AMT'12 Proceedings of the 8th international conference on Active Media Technology
JIRL - A C++ Library for JPEG Compressed Domain Image Retrieval
ISM '12 Proceedings of the 2012 IEEE International Symposium on Multimedia
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Since there are few open image retrieval toolkits available, researchers in the field are often forced to re-implement existing algorithms in order to perform a comparative evaluation. None of the existing toolkits support retrieval of JPEG images directly in the compressed domain. The authors' aim is therefore to facilitate the use of compressed domain image retrieval techniques as well as ease retrieval evaluation by fellow researchers. For this purpose, the authors present JIRL, an open source C++ software suite that allows content-based image retrieval in the JPEG compressed domain and provides tools for benchmarking retrieval accuracy and retrieval time. In total, twelve state-of-the-art JPEG retrieval algorithms are implemented, while for each method techniques for compressed domain feature extraction as well as feature comparison are provided in an object-oriented framework. An example image retrieval application is also provided to demonstrate how the library can be used. JIRL is made available to fellow researchers under the LGPL v.2.1 license.