skip to main content
10.1145/1141277.1141289acmconferencesArticle/Chapter ViewAbstractPublication PagessacConference Proceedingsconference-collections
Article

Dynamic interactive spatial similarity retrieval in iconic image databases using enhanced digraph

Published:23 April 2006Publication History

ABSTRACT

Similarity-based retrieval of images is an important task in many image database applications. Interactive similarity retrieval is one way to resolve the fuzzy area involving psychological and physiological factors of individuals during the retrieval process. A good interactive similarity system is not only dependent on a good measure system, but also closely related to the structure of the image database and the retrieval process based on the respective image database structure. In this paper, we propose to use a dynamic similarity measure on top of the enhanced digraph index structure for interactive iconic image similarity retrieval. Our approach makes use of the multiple feedbacks from the user to get the hidden subjective information during the retrieval process, and avoids the high cost of re-computation of an interactive retrieval algorithm.

References

  1. Ang, C. H., Ling, T. W. and Zhou, X. M., Qualitative spatial relationships representation IO&T and its retrieval, 9th International Conference, DEXA '98, Vienna, Austria, August 1998. Lecture Notes in Computer Science 1460, 270--279. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bartolini, I., Ciaccia, P. and Wass, F., FeedbackBypass: A new approach to interactive similarity query processing, Proc. of the 27th VLDB Conference, 201--210, Roma, Italy, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Chang, C. C., Spatial match retrieval of symbolic pictures, Journal of Information Science and Engineering, Vol. 7, 405--422, 1991.Google ScholarGoogle Scholar
  4. Chang, C. C., A fast algorithm to retrieve symbolic pictures, International Journal of Computer Mathematics, Vol. 43, No. 1, 133--138, 1992.Google ScholarGoogle ScholarCross RefCross Ref
  5. Chang, E., Li, B. and Li, C., Towards perception-based image retrieval, IEEE Content-Based Access of Image and Video Libraries, 010--105, June 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Chang, S. K., Shi, Q. Y. and Yan, C. W., Iconic indexing by 2D strings. IEEE Trans. on Pattern Recognition and Machine Intelligence, Vol. 9, No. 3, 413--428, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Ciaccia, P., Patella, M., and Zezula, P., M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. Proc. of the 23rd VLDB Conference, 426--435, Athens, Greece, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Di Sciascio, E., Donini, F. M. and Mongiello, M., Spatial layout representation for query-by-sketch content-based image retrieval, Pattern Recognition Letters, Vol. 23, No. 13, 1599--1612, November 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. El-Kwae, E. A., and Kabuka, M. R., A robust framework for content-based retrieval by spatial similarity in image database, ACM Transactions on Information Systems, Vol. 17, No. 2, 174--198, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. El-Kwae, E. A., and Kabuka, M. R., Efficient content-based indexing of large image databases, ACM Transactions on Information Systems, Vol. 18, No. 2, 171--210, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Ishikawa, Y., Subramanya, R., and Faloutsos, C., Mindreader: Querying databases through multiple examples, Proc. of the 24rd VLDB Conference, 218--227, New York City, New York, USA, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Nabil, M., Ngu, A. H. H. and Sheperd, J., Picture similarity retrieval using 2D projection interval representation. IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 4, 533--539, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Porkaew, K., Chakrabarti, K., and Mehrotra, S., Query refinement for multimedia similarity in MARS, ACM International Multimedia Conference, 235--238, Orlando, Florida, USA, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Rui, Y., Huang, T. S., Ortega, M. and Mehrotra, S., Relevance feedback: A power tool for interactive content-based image retrieval, IEEE Transaction on Circuits and Video Technology, 8(5): 644--655, September 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Zhou, X. M., Ang, C. H. and Ling, T. W., Indexing iconic image database for interactive spatial similarity retrieval, 9th International Conference on Database Systems for Advanced Applications, DASFAA 2004, Jeju Island, Korea, March 2004. Lecture Notes in Computer Science 2973, 314--324.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Dynamic interactive spatial similarity retrieval in iconic image databases using enhanced digraph

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      SAC '06: Proceedings of the 2006 ACM symposium on Applied computing
      April 2006
      1967 pages
      ISBN:1595931082
      DOI:10.1145/1141277

      Copyright © 2006 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 23 April 2006

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • Article

      Acceptance Rates

      Overall Acceptance Rate1,650of6,669submissions,25%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader