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Region-Based Image Retrieval Using Multiple-Features

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Book cover Recent Advances in Visual Information Systems (VISUAL 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2314))

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Abstract

Content-based image retrieval from large multimedia databases effectively and efficiently is a challenging task. In this paper, we propose a retrieval technique that utilizes the regional properties of the images. After image segmentation, each region is represented by its colour, shape, size, and spatial position. Regions of different images are matched and a distance measure between the whole images is calculated. The relative importance of the above features is investigated, and colour plays a major role in the process of distance computation. Our representation is robust to minor inaccuracy in image segmentation, is invariant to scaling and can perceive geometric changes like translation and rotation. The experimental results indicate that our technique outperforms recently proposed techniques.

Work partially supported by the Canadian Natural Sciences and Engineering Research Council (NSERC).

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References

  1. J. Ashley, R. Barber, M. Flickner, J. Hafner, D. Lee W. Niblack, and D. Petkovic. Automatic and semi-automatic methods for image annotation and retrieval in qbic. In In Proc. Storage and Retrieval for Image and Video Databases II, pages 24–35, 1995.

    Google Scholar 

  2. A. D. Bimbo. Visual Information Retrieval. Morgan Kaufmann Ed, 1999.

    Google Scholar 

  3. C. Carson, M. Thomas, S. Belongie, J.M. Hellerstein, and J. Malik. Blobworld: A system for region-based image indexing and retrieval. In In Proc. 3 rd Intl. Conf. on Visual Information Systems, pages 509–516, 1999.

    Google Scholar 

  4. D. Comaniciu and P. Meer. Robust analysis of feature spaces: Color image segmentation. In In Proc. IEEE Conf. on Comp. Vis. and Pattern Recognition, pages 750–755, 1997.

    Google Scholar 

  5. R. C. Gonzalez and R. E. Woods. Digital Image Processing. Addison-Wesley, third edition, 1992.

    Google Scholar 

  6. J. Han and M. Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann, 2000.

    Google Scholar 

  7. W. Hsu, T.S. Chua, and H.K. Pung. An integrated color-spatial approach to content-based image retrieval. In In Proc. 3 rd ACM Multimedia Conf., pages 305–313, 1995.

    Google Scholar 

  8. M. K Hu. Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, IT-8:179–187, 1962.

    Google Scholar 

  9. T. Huang and Y. Rui. Image retrieval: Past, present, and future. In In Proc. Intl. Symposium on Multimedia Information Processing, pages 1–23, 1997.

    Google Scholar 

  10. P. Kerminen and M. Gabbouj. Image retrieval based on color matching. In Finnish Signal Processing Symp., pages 89–93, 1999.

    Google Scholar 

  11. J. Li, J. Z. Wang, and G. Wiederhold. IRM: integrated region matching for image retrieval. In ACM Multimedia, pages 147–156, 2000.

    Google Scholar 

  12. W.Y. Ma and B. S. Manjunath. Netra: A toolbox for navigating large image databases. Multimedia Systems, 7(3):184–198, 1999.

    Article  Google Scholar 

  13. F. Mokhtarian, S. Abbasi, and J. Kittler. Efficient and robust retrieval by shape content through curvature scale space. In In Proc. Intl. Workshop on Image Databases and Multimedia Search, pages 35–42, 1996.

    Google Scholar 

  14. G. Pass and R. Zabih. Histogram refinement for content-based image retrieval. In Workshop on Applications of Computer Vision, pages 96–102, 1996.

    Google Scholar 

  15. G. Pass, R. Zabih, and J. Miller. Comparing images using color coherence vectors. In Proc. of the ACM Multimedia’96 Intl. Conf., pages 65–73, 1996.

    Google Scholar 

  16. Y. Rui, A. She, and T. Huang. Modified fourier descriptors for shape representation-a practical approach. In In Proc. 1 st Intl. Workshop on Image Databases and Multimedia Search., pages 22–23, 1996.

    Google Scholar 

  17. J. Smith and S. Chang. Single color extraction and image query. In In Proc. IEEE Int. Conf. on Image Proc., pages 528–531, 1995.

    Google Scholar 

  18. R. O. Stehling, M. A. Nascimento, and A. X. Falcao. Techniques for color-based image retrieval. Technical Report 16, University of Alberta, 2001.

    Google Scholar 

  19. R.O. Stehling, M.A. Nascimento, and A.X Falcao. An adaptive and efficient clustering-based approach for content based image retrieval in image databases. In In Proc. Intl. Data Eng. and Application Symposium, pages 356–365, 2001.

    Google Scholar 

  20. M.A. Stricker and M. Orengo. Similarity of color images. In In Proc. Storage and Retrieval for Image and Video Databases (SPIE), pages 381–392, 1995.

    Google Scholar 

  21. J.Z. Wang, J. Li, and G. Wiederhold. Simplicity: Semantics-sensitive integrated matching for picture libraries. IEEE Trans. on Pattern Analysis and Machine Intelligence, 23(9):947–963, 2001.

    Article  Google Scholar 

  22. I. Witten, A. Moffat, and T. Bell. Managing Gigabytes. Morgan Kaufmann, Second edition, 1999.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computing Science, University of Alberta, Canada

    Veena Sridhar, Mario A. Nascimento & Xiaobo Li

Authors
  1. Veena Sridhar
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  2. Mario A. Nascimento
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  3. Xiaobo Li
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Editor information

Editors and Affiliations

  1. Knowledge Systems Institute, 3420 Main Street, 60076, Skokie, IL, USA

    Shi-Kuo Chang

  2. Dept. of Comp. Science & Information Engineering, National Chiao Tung University, 1001 Ta HsuehRoad, Hsin Chu, Taiwan

    Zen Chen  & Suh-Yin Lee  & 

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© 2002 Springer-Verlag Berlin Heidelberg

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Sridhar, V., Nascimento, M.A., Li, X. (2002). Region-Based Image Retrieval Using Multiple-Features. In: Chang, SK., Chen, Z., Lee, SY. (eds) Recent Advances in Visual Information Systems. VISUAL 2002. Lecture Notes in Computer Science, vol 2314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45925-1_6

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  • DOI: https://doi.org/10.1007/3-540-45925-1_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43358-3

  • Online ISBN: 978-3-540-45925-5

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