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A Fast Image Retrieval Using the Unification Search Method of Binary Classification and Dimensionality Condensation of Feature Vectors

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Book cover Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3683))

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Abstract

We present the two-stage content-based image retrieval as a new fast image retrieval approach using the unification search method of binary classification and dimensionality condensation of feature vectors. The method successfully reduces the overall retrieval time, while maintaining the same retrieval relevance as the conventional exhaustive search method. By the extensive computer simulations, we have observed that the method is more effective as user-specific threshold for the similarity score increase.

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Author information

Authors and Affiliations

  1. Department of Computer Education, College of Education, Cheju National University, 66 Jejudaehakno, Jeju-si, Jeju-do, 690-756, Korea

    Jungwon Cho

  2. Multimedia Laboratory, Department of Electrical and Computer Engineering, Hanyang University, 17 Haengdang-dong, Sungdong-gu, Seoul, 133-791, Korea

    Seungdo Jeong

  3. Division of Information and Communications, Hanyang University, 17 Haengdang-dong, Sungdong-gu, Seoul, 133-791, Korea

    Byunguk Choi

Authors
  1. Jungwon Cho
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  2. Seungdo Jeong
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  3. Byunguk Choi
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Cho, J., Jeong, S., Choi, B. (2005). A Fast Image Retrieval Using the Unification Search Method of Binary Classification and Dimensionality Condensation of Feature Vectors. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_35

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  • DOI: https://doi.org/10.1007/11553939_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28896-1

  • Online ISBN: 978-3-540-31990-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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