Abstract
In this paper we introduce a low complexity and accurate technique for target image search and retrieval. This method, which operates directly in the compressed JPEG domain, addresses two of the CBIR challenges stated by The Benchathlon Network regarding the search of a specific image: finding out if an exact same image exists in a database, and identifying this occurrence even when the database image has been compressed with a different coding bit-rate. The proposed technique can be applied in feature-containing or featureless image collections, and thus it is also suitable to search for image copies that might exist on the Web for law enforcement of copyrighted material. The reported method exploits the fact that the phase of the Discrete Cosine Transform coefficients contains a significant amount of information of a transformed image. By processing only the phase part of these coefficients, a simple, fast, and accurate target image search and retrieval technique is achieved.
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References
Smith, B.C., Rowe, L.A.: Compressed domain processing of JPEG-encoded images. Real-Time Imaging J. 2(1), 3–17 (1996)
Mandal, M.K., Idris, F., Panchanathan, S.: A critical evaluation of image and video indexing techniques in the compressed domain. Image and Vision Computing Journal, Special issue on Content Based Image Indexing 17(7), 513–529 (1999)
Wong, P.H.W., Au, O.C.: A blind watermarking technique in JPEG compressed domain. In: Proc. IEEE Int’l Conf. on Image Processing (ICIP 2002), vol. 3, pp. 497–500 (September 2002)
The Benchathlon Network: CBIR Challenges –, http://www.benchathlon.net/resources/challenges.html
Cox, I.J., Miller, M.L., Minka, T.P., Papathomas, T.V., Yianilos, P.N.: The Bayesian image retrieval system, PicHunter: Theory, implementation, and psychophysical experiments. IEEE Trans. on Image Processing 9(1), 20–37 (2000)
Image-SeekerTM–, http://www.ltutech.com
AcdseeTM–, http://www.acdsee.com
Feng, G., Jiang, J.: JPEG image retrieval based on features from the DCT domain. In: Lew, M., Sebe, N., Eakins, J.P. (eds.) CIVR 2002. LNCS, vol. 2383, pp. 120–128. Springer, Heidelberg (2002)
Smith, J.R., Chang, S.-F.: Transform features for texture classification and discrimination in large image databases. In: Proc. IEEE Int’l Conf. on Image Processing (ICIP 1994), vol. 3, pp. 407–411 (November 1994)
Lay, J.A., Guan, L.: image retrieval based on energy histograms of the low frequency DCT coefficients. In: Proc. IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP 1999), vol. 6, pp. 3009–3012 (March 1999)
Armstrong, A., Jiang, J.: An efficient image indexing algorithm in JPEG compressed domain. In: Proc. IEEE Int’l Conf. on Consumer Electronics (ICCE 2001), pp. 25–30 (June 2001)
Jiang, J., Armstrong, A., Feng, G.C.: Web-based image indexing and retrieval in JPEG compressed domain. Multimedia Systems 9, 424–432 (2004)
Panchanathan, S.: Compressed or progressive image search. In: Castelli, V., Bergman, L. (eds.) Image Databases, Search and Retrieval of Digital Imagery. ch. 16. John Wiley & Sons, USA (2002)
del Bimbo, A.: Visual Information Retrieval. Morgan Kaufman Publ., USA (1999)
Manolopoulos, Y., Theodoridis, Y., Esotras, V.J.: Advanced database indexing. Kluwer Academia Publishers, USA (1999)
Johnson, N.F.: In: search of the right image: Recognition and tracking of images in image databases, collections, and the Internet, Technical Report, CSIS-TR-99-05-NFS, Center for Secure Information Systems, George Mason University, Fairfax, VA, USA (April 1999)
Guru, D.S., Punitha, P.: An invariant scheme for exact match retrieval of symbolic images based upon principal component analysis. Pattern Recognition Letters 25(1), 73–86 (2004)
Chang, C.-C., Wu, T.-C.: An exact match retrieval scheme based upon principal component analysis. Pattern Recognition Letters 16(5), 465–470 (1995)
Bosch, P., van Ballegooij, A., de Vries, A., Kersten, M.: Exact matching in image databases. In: Proc. IEEE Int’l Conf. on Multimedia and Expo (ICME 2001), pp. 513–516 (August 2001)
Bracamonte, J.: The DCT-phase of images and its applications, Technical Report IMT No. 451 PE 01/04, Institute of Microtechnology, University of Neuchâtel, Switzerland (January 2004)
Bracamonte, J., Ansorge, M., Pellandini, F., Farine, P.-A.: Low complexity image matching in the compressed domain by using the DCT-phase. In: Proc. of the 6th COST 276 Workshop on Information and Knowledge Management for Integrated Media Communications, Thessaloniki, Greece, pp. 88–93 (May 2004)
Wang, J.: Downloads/Related Links –, http://wang.ist.psu.edu/docs/related
Pennebaker, W.B., Mitchel, J.L.: JPEG Still Image Data Compression Standard, Van Nostrand Reinhold, USA (1993)
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Bracamonte, J., Ansorge, M., Pellandini, F., Farine, PA. (2005). Efficient Compressed Domain Target Image Search and Retrieval. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_19
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DOI: https://doi.org/10.1007/11526346_19
Publisher Name: Springer, Berlin, Heidelberg
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