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A Region-Based Representation of Images in MARS

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Abstract

We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propose new image coding techniques which combine a wavelet representation, embedded coding of the wavelet coefficients, and segmentation of image-domain regions in the wavelet domain. A bitstream is generated in which each image region is encoded independently of other regions, without having to explicitly store information describing the regions. Simulation results show that our proposed algorithms achieve coding performance which compares favorably, both perceptually and objectively, to that achieved using state-of-the-art image/video coding techniques while additionally providing region-based support.

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References

  1. W. Niblack et al., “The QBIC project: Querying images by content using color, texture and shape,” Proceedings of the SPIE Storage and Retrieval for Image and Video Databases Conference, 1994.

  2. C. Faloutsos, M. Flickner, W. Niblack, D. Petkovic, W. Equitz, and R. Barber, “Efficient and effective querying by image content,” Technical report, IBM Almaden Research Center, 1993.

  3. M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker, “Query by image and video content: The QBIC system,” IEEE Computer, Sept. 1995.

  4. R. Jain,“Workshop report: NSFworkshop on visual information management systems,” Proceedings of the SPIE Storage and Retrieval for Image and Video Databases Conference, 1993.

  5. R. Jain, A. Pentland, and D. Petkovic, NSF-ARPA workshop on visual information management systems, 1995.

  6. J.R. Bach, C. Fuller, A. Gupta, A. Hampapur, B. Horowitz, R. Humphrey, R. Jain, and C.-F. Shu, “The virage image search engine: An open framework for image management,” Proceedings of the SPIE Storage and Retrieval for Image and Video Databases Conference, 1996.

  7. J. Dowe, “Content-based retrieval in multimedia imaging,” Proceedings of the SPIE Storage and Retrieval for Image and Video Databases Conference, 1993.

  8. T.S. Huang, S. Mehrotra, and K. Ramchandran, “Multimedia analysis and retrieval system (MARS) project,” Proceedings of the 33rd Annual Clinic on Library Application of Data Processing-Digital Image Access and Retrieval, 1996.

  9. W.Y. Ma and B.S. Manjunath, “Netra: A toolbox for navigating large image databases,” Proceedings of the IEEE International Conference on Image Processing, Santa Barbara, CA, 1997.

  10. M.K. Mandal, T. Aboulnasr, and S. Panchanathan, “Image indexing using moments and wavelets,” IEEE Transactions on Consumer Electronics, Vol. 42, No.3, pp. 557-565, Aug. 1996.

    Article  Google Scholar 

  11. A. Pentland, R.W. Picard, and S. Sclaroff, “Photobook: Contentbased manipulation of image databases,” International Journal of Computer Vision, Vol. 18, No.3, pp. 233-254, 1996.

    Article  Google Scholar 

  12. J.R. Smith and S.-F. Chang, “Visually searching the web for content,” IEEE Multimedia Magazine, Vol. 4, No.3, pp. 12-20, Summer 1997.

    Article  Google Scholar 

  13. MPEG-7 Applications Document, ISO/IEC JTC1/SC29/WG11 N1922, MPEG97, 1997.

  14. MPEG-7: Context and Objectives (V.5), ISO/IEC JTC1/SC29/WG11 N1920, MPEG97, 1997.

  15. Third Draft of MPEG-7 Requirements, ISO/IEC JTC1/SC29/WG11 N1921, MPEG97, 1997.

  16. M. Ortega, Y. Rui, K. Chakrabarti, S. Mehrotra, and T.S. Huang, “Supporting similarity queries in MARS,” Proceedings of the ACM Conference on Multimedia, Seattle, WA, 1997.

  17. Y. Rui, T.S. Huang, and S. Mehrotra, “Relevance feedback techniques in interactive content-based image retrieval,” Proceedings of the IS&T SPIE Storage and Retrieval of Images/Video Databases VI, EI'98, 1998.

  18. Y. Rui, T.S. Huang, S. Mehrotra, and M. Ortega, “A relevance feedback architecture in content-based multimedia information retrieval systems,” Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries, held in conjunction with the IEEE Computer Vision and Pattern Recognition Conference, San Juan, Puerto Rico, 1997.

  19. Y. Rui, A.C. She, and T.S. Huang, “Automated shape segmentation using attraction-based grouping in spatial-color-texture space,” Proceedings of the IEEE International Conference on Image Processing, 1996.

  20. S. Servetto, K. Ramchandran, and M. Orchard, “Image coding based on a morphological representation of wavelet data,” IEEE Transactions on Image Processing, Dec. 1996, to appear.

  21. S. Mehrotra, K. Chakrabarti, M. Ortega, Y. Rui, and T.S. Huang, “Multimedia analysis and retrieval system,” Proceedings of the 3rd International Workshop on Information Retrieval Systems, 1997.

  22. C. Buckley and G. Salfon, “Optimization of relevance feedback weights,” Proceedings of the 18th International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, WA, 1995.

  23. G. Salfon and M.J. McGill, Introduction to Modern Information Retrieval, McGraw-Hill Book Company, 1983.

  24. Y. Rui, K. Chakrabarti, S. Mehrotra, Y. Zhao, and T.S. Huang, “Dynamic clustering for optimal retrieval in high dimensional multimedia databases,” Technical report TR-MARS-10-97, IFP Group, Beckman Institute, University of Illinois at Urbana-Champaign, 1997.

    Google Scholar 

  25. M. Hansen and W. Higgins, “Watershed-driven relaxation labeling for image segmentation,” Proceedings of the IEEE International Conference on Image Processing, 1994.

  26. T. Gevers and V. Kajcovski, “Image segmentation by directed region subdivision,” Proceedings of the IEEE International Conference on Image Processing, 1994.

  27. Alfred C. She and Thomas S. Huang, “Segmentation of road scenes using color and fractal-based texture classification,” Proceedings of the IEEE International Conference on Image Processing, 1994.

  28. W.Y. Ma and B.S. Manjunath, “Edge flow: A framework of boundary detection and image segmentation,” Proceedings of IEEE Computer Vision and Pattern Recognition Conference, 1997.

  29. M. Swain and D. Ballard, “Color indexing,” International Journal of Computer Vision, Vol. 7, No.1, 1991.

  30. Y. Rui, T.S. Huang, S. Mehrotra, and M. Ortega, “Automatic matching tool selection using relevance feedback in MARS,” Proceedings of the 2nd International Conference on Visual Information Systems, 1997.

  31. M. Vetterli and J. Kovacvic, Wavelets and Subband Coding, 1st edition, Prentice Hall, Englewoods Cliffs, NJ, 1995.

    MATH  Google Scholar 

  32. A. Said and W. Pearlman, “A new, fast, and efficient image codec based on set partitioning in hierarchical trees,” IEEE Transactions on Circuits and Systems forVideo Technology, Vol. 6, No.3, pp. 243-250, June 1996.

    Article  Google Scholar 

  33. J. Shapiro, “Embedded image coding using zerotrees of wavelet coefficients,” IEEE Transactions on Signal Processing, Vol. 41, No.12, pp. 3445-3462, Dec. 1993.

    Article  MATH  Google Scholar 

  34. Z. Xiong, K. Ramchandran, and M. Orchard, “Space-frequency quantization for wavelet image coding,” IEEE Transactions on Image Processing, Vol. 6, No.5, pp. 677-693, May 1997.

    Article  Google Scholar 

  35. N. Ahmed, T. Natarajan, and K.R. Rao, “Discrete cosine transform,” IEEE Transactions on Computers, Vol. 23, pp. 88-93, Jan. 1974.

    MathSciNet  Google Scholar 

  36. X. Yang and K. Ramchandran, “Hierarchical backward motion compensation for wavelet video coding using optimized interpolation filters,” Proceedings of the IEEE International Conference on Image Processing, Santa Barbara, CA, 1997.

  37. P. Maragos and R. Schafer, “Morphological systems for multidimensional signal processing,” Proceedings of the IEEE, Vol. 78, No.4, pp. 690-710, April 1990.

    Article  Google Scholar 

  38. K. Ramchandran and M. Orchard, “An investigation of waveletbased image coding using an entropy-constrained quantization framework,” IEEE Transactions on Signal Processing, Vol. 46, No.2, pp. 342-353, Feb. 1998.

    Article  MathSciNet  Google Scholar 

  39. D. Taubman and A. Zakhor, “Multirate 3-D subband coding of video,” IEEE Transactions on Image Processing, Vol. 3, No.5, pp. 572-588, Sept. 1994.

    Article  Google Scholar 

  40. W. Equitz and T. Cover, “Successive refinement of information,” IEEE Transactions on Information Theory, Vol. 37, No.2, pp. 269-275, March 1991.

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801

    Sergio D. Servetto, Yong Rui, Kannan Ramchandran & Thomas S. Huang

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  1. Sergio D. Servetto
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  2. Yong Rui
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  3. Kannan Ramchandran
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  4. Thomas S. Huang
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Servetto, S.D., Rui, Y., Ramchandran, K. et al. A Region-Based Representation of Images in MARS. The Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology 20, 137–150 (1998). https://doi.org/10.1023/A:1008026508931

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