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Australasian Joint Conference on Artificial Intelligence

AI 2003: AI 2003: Advances in Artificial Intelligence pp 633–640Cite as

Automatic Fingerprint Center Point Determination by Using Modified Directional Field and Morphology

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 2903)

Abstract

Accurate and reliable center point determination of the fingerprint is an essential pre-processing step for the image based fingerprint recognition approach. This step is particularly important since a reference point is required to cancel the variation in position of the reference and testing fingerprint image. This paper illustrated an automatic center point determination algorithm that couples the modified averaged square directional field (MASDF) with morphol-ogical operation, in order to pinpoint the center point of the fingerprint efficiently and accurately. The experiment result shows only 3.13% rejection rate for the false center point by using the proposed method.

Keywords

  • Center Point
  • Rejection Rate
  • Morphological Operation
  • Fingerprint Image
  • Speed Factor

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-540-24581-0_54
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References

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Author information

Authors and Affiliations

  1. Faculty of Information Science and Technology (FIST), Multimedia University Jalan Ayer Keroh Lama, Bukit Beruang, 75450, Melaka, Malaysia

    T. B. J. Andrew, T. S. Ong, N. C. L. David & Y. W. Sek

Authors
  1. T. B. J. Andrew
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  2. T. S. Ong
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  3. N. C. L. David
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  4. Y. W. Sek
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Australian National University, ACT 0200, Acton, Australia

    Tamás (Tom) Domonkos Gedeon

  2. Murdoch University,  

    Lance Chun Che Fung

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© 2003 Springer-Verlag Berlin Heidelberg

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Andrew, T.B.J., Ong, T.S., David, N.C.L., Sek, Y.W. (2003). Automatic Fingerprint Center Point Determination by Using Modified Directional Field and Morphology. In: Gedeon, T.(.D., Fung, L.C.C. (eds) AI 2003: Advances in Artificial Intelligence. AI 2003. Lecture Notes in Computer Science(), vol 2903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24581-0_54

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  • DOI: https://doi.org/10.1007/978-3-540-24581-0_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20646-0

  • Online ISBN: 978-3-540-24581-0

  • eBook Packages: Springer Book Archive