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Efficient Palmprint Search Based on Database Clustering for Personal Identification

  • Conference paper
Knowledge and Systems Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 326))

Abstract

This paper proposes an efficient palmprint searching algorithm for personal identification based on database clustering, which reduces the search space of fine matching. A complex filter is applied to double orientation field to detect the symmetry of the palm lines as the main feature at coarse-level search. A K-means clustering technique is applied to partition the symmetry feature space into clusters. A query processing is proposed to facilitate an efficient searching. The experimental results on the public database of Hong Kong Polytechnic University show the effectiveness of the proposed searching algorithm.

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, Ho Chi Minh City University of Technology, Ho Chi Minh City, VietNam

    Hoang Thien Van

  2. Department of Computer Sciences, Ho Chi Minh University of Science, Ho Chi Minh City, VietNam

    Thai Hoang Le

Authors
  1. Hoang Thien Van
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  2. Thai Hoang Le
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Corresponding author

Correspondence to Hoang Thien Van .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Viet-Ha Nguyen

  2. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Anh-Cuong Le

  3. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

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© 2015 Springer International Publishing Switzerland

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Thien Van, H., Hoang Le, T. (2015). Efficient Palmprint Search Based on Database Clustering for Personal Identification. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_31

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  • DOI: https://doi.org/10.1007/978-3-319-11680-8_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11679-2

  • Online ISBN: 978-3-319-11680-8

  • eBook Packages: EngineeringEngineering (R0)

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