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Optimal Core Point Detection Using Multi-scale Principal Component Analysis

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Book cover Mining Intelligence and Knowledge Exploration (MIKE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9468))

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Abstract

Core point plays a vital role in fingerprint matching and classification. The fingerprint images may be of poor quality because of sensor type and user’s body condition. To detect the core point in noisy and poor quality fingerprint images, we have estimated the dominant orientation field based on principal component analysis and multi-scale pyramid decomposition to produce correct orientation field. The proposed work detects the optimal upper and lower core points using shape analysis of orientation field and binary candidate region images in fingerprints. Experiments are carried out on FVC databases and it is found that the proposed algorithm has high accuracy in locating exact core points.

T. Kathirvalavakumar–This work is Funded by University Grants Commission Major Research Project, New Delhi, INDIA.

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Author information

Authors and Affiliations

  1. Research Center in Computer Science, V.H.N.S.N. College (Autonomous), Virudhunagar, 626 001, India

    T. Kathirvalavakumar

  2. Department of Computer Science, N.M.S.S.Vellaichamy Nadar College (Autonomous), Madurai, 625 019, India

    K. S. Jeyalakshmi

Authors
  1. T. Kathirvalavakumar
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  2. K. S. Jeyalakshmi
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Corresponding author

Correspondence to T. Kathirvalavakumar .

Editor information

Editors and Affiliations

  1. Norwegian Univ. of Science & Technology, Trondheim, Norway

    Rajendra Prasath

  2. Intl Inst of Info Tech Hyderabad, Hyderabad, India

    Anil Kumar Vuppala

  3. V.H.N.S.N.College (Autonomous), Virudhunagar, Tamil Nadu, India

    T. Kathirvalavakumar

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Kathirvalavakumar, T., Jeyalakshmi, K.S. (2015). Optimal Core Point Detection Using Multi-scale Principal Component Analysis. In: Prasath, R., Vuppala, A., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2015. Lecture Notes in Computer Science(), vol 9468. Springer, Cham. https://doi.org/10.1007/978-3-319-26832-3_19

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  • DOI: https://doi.org/10.1007/978-3-319-26832-3_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26831-6

  • Online ISBN: 978-3-319-26832-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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