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Blobworld: A System for Region-Based Image Indexing and Retrieval

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Visual Information and Information Systems (VISUAL 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1614))

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Abstract

Blobworld is a system for image retrieval based on finding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions (“blobs”) with associated color and texture descriptors. Queryingi s based on the attributes of one or two regions of interest, rather than a description of the entire image. In order to make large-scale retrieval feasible, we index the blob descriptions using a tree. Because indexing in the high-dimensional feature space is computationally prohibitive, we use a lower-rank approximation to the high-dimensional distance. Experiments show encouraging results for both querying and indexing.

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References

  1. Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: An efficient and robust access method for points and rectangles. In Proc. ACM-SIGMOD Int’l Conf. on Management of Data (1990) 322–331

    Google Scholar 

  2. Belongie, S., Carson, C., Greenspan, H., Malik, J.: Color-and texture-based image segmentation using EM and its application to content-based image retrieval. In Proc. Int. Conf. Comp. Vis. (1998)

    Google Scholar 

  3. Carson, C., Thomas, M., Belongie, S., Hellerstein, J., Malik, J.: Blobworld: A system for region-based image indexing and retrieval. Technical Report UCB/CSD-99-1041.

    Google Scholar 

  4. Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data via the EM algorithm. J. Royal Statistical Soc., Ser. B, 39 (1977) 1–38

    MATH  MathSciNet  Google Scholar 

  5. Enser, P.: Query analysis in a visual information retrieval context. J. Doc. and Text Management, 1 (1993) 25–52

    Google Scholar 

  6. Flickner, M., Sawhney, H., Niblack, W., Ashley, J., et al: Query by image and video content: The QBIC system. IEEE Computer, 28 (Sept. 1995) 23–32

    Google Scholar 

  7. Gupta, A., Jain, R.: Visual information retrieval. Comm. Assoc. Comp. Mach., 40 (May 1997) 70–79

    Google Scholar 

  8. Hafner, J., Sawhney, H., Equitz, W., Flickner, M., Niblack, W.: Efficient color histogram indexing for quadratic form distance functions. IEEE Trans. Pattern Analysis and Machine Intelligence, 17 (July 1995) 729–736

    Article  Google Scholar 

  9. Hellerstein, J. M., Naughton, J., Pfeffer, A.: Generalized search trees for database systems. In Proc. 21st Int. Conf. on Very Large Data Bases (1995) 562–573

    Google Scholar 

  10. Hjaltason, G., Samet, H.: Rankingin spatial databases. In Proc. 4th Int. Symposium on Large Spatial Databases (1995) 83–95

    Google Scholar 

  11. Jacobs, C., Finkelstein, A., Salesin, D.: Fast multiresolution image querying. In Proc. SIGGRAPH (1995)

    Google Scholar 

  12. Lipson, P., Grimson, E., Sinha, P.: Configuration based scene classification and image indexing. In Proc. IEEE Comp. Soc. Conf. Comp. Vis. and Patt. Rec., (1997) 1007–1013

    Google Scholar 

  13. Ma, W., Manjunath, B.: NeTra: A toolbox for navigating large image databases. In Proc. IEEE Int. Conf. on Image Proc., (1996) 568–571

    Google Scholar 

  14. Ogle, V., Stonebraker, M.: Chabot: Retrieval from a relational database of images. IEEE Computer, 28 (Sept. 1995) 40–48

    Google Scholar 

  15. Pentland, A., Picard, R., Sclaroff, S.: Photobook: Content-based manipulation of image databases. Int. J. Comp. Vis., 18 (1996) 233–254

    Article  Google Scholar 

  16. Rissanen, J.: Stochastic Complexity in Statistical Inquiry. World Scientific (1989)

    Google Scholar 

  17. Berchtold, D. K. S., Kriegel, H.: The x-tree: An index structure for high-dimensional data. In Proc. of the 22nd VLDB Conference (1996) 28–39

    Google Scholar 

  18. Smith, J. R., Chang, S.-F.: Single color extraction and image query. In Proc. IEEE Int. Conf. on Image Processing (1995) 528–531

    Google Scholar 

  19. White, D., Jain, R.: Similarity indexing with the ss-tree. In Proc. 12th IEEE Int’l Conf. on Data Engineering (1996) 516–523

    Google Scholar 

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© 1999 Springer-Verlag Berlin Heidelberg

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Carson, C., Thomas, M., Belongie, S., Hellerstein, J.M., Malik, J. (1999). Blobworld: A System for Region-Based Image Indexing and Retrieval. In: Huijsmans, D.P., Smeulders, A.W.M. (eds) Visual Information and Information Systems. VISUAL 1999. Lecture Notes in Computer Science, vol 1614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48762-X_63

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  • DOI: https://doi.org/10.1007/3-540-48762-X_63

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66079-8

  • Online ISBN: 978-3-540-48762-3

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