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Space Transformation Based Approach for Effective Content-Based Image Retrieval

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Foundations of Intelligent Systems (ISMIS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2871))

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Abstract

In this paper, we extend the work done by Choubey and Raghavan, which proposed an approach to content-based image retrieval that uses the space transformation methods proposed by Goldfarb to transform the original low-level image space into a feature space, where images are represented as vectors of high-level features that enable efficient query processing. The resulting retrieval system consists of three phases: database population, online addition and image retrieval. In the current work, we investigate issues relating to online addition of new images, during database population phase, in incremental stages. The results show that our approach is effective in retrieving images even when the image database is dynamic.

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References

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Author information

Authors and Affiliations

  1. University of Louisiana at Lafayette, CACS, P.O.Box 44330, Lafayette, LA, 70503, USA

    Biren Shah & Vijay Raghavan

Authors
  1. Biren Shah
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  2. Vijay Raghavan
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Editor information

Editors and Affiliations

  1. The International WIC Institute, Beijing University of Technology, China

    Ning Zhong

  2. Department of Computer Science, University of North Carolina, NC 28223, Charlotte, USA

    Zbigniew W. Raś

  3. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  4. Department of Informatics, Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi, 819-0395, Fukuoka, Japan

    Einoshin Suzuki

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© 2003 Springer-Verlag Berlin Heidelberg

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Shah, B., Raghavan, V. (2003). Space Transformation Based Approach for Effective Content-Based Image Retrieval. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_71

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  • DOI: https://doi.org/10.1007/978-3-540-39592-8_71

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20256-1

  • Online ISBN: 978-3-540-39592-8

  • eBook Packages: Springer Book Archive

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