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Fingerprint Reference Point Detection Based on High Curvature Points

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Data Mining and Big Data (DMBD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

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Abstract

The problem considered in this paper is associated with the image processing and the design of algorithm which allows selecting reference point on the fingerprint image. The reference point is used to align between the fingerprints in the fingerprint authentication systems faster than the conventional techniques. The reference point is the point with maximum curvature on the friction ridge, which is usually located in the central fingerprint area. Fingerprint homogeneous ridges are extracted from the image and then are processed by the IPAN99 algorithm which allows to detect curvatures of these lines.

The experimental results on datasets of FVC2000, FVC2002, FVC2004 and NIST, show the high efficiency and satisfactory accuracy of the proposed algorithm. Proposed solution allows detecting reference points more precisely than other algorithms.

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Notes

  1. 1.

    http://bias.csr.unibo.it/fvc2000/databases.asp.

  2. 2.

    http://bias.csr.unibo.it/fvc2002/databases.asp.

  3. 3.

    http://bias.csr.unibo.it/fvc2004/databases.asp.

  4. 4.

    http://www.nist.gov/itl/iad/ig/special_dbases.cfm.

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Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, ul. Bedzinska 39, 41-200, Sosnowiec, Poland

    Krzysztof Wrobel, Rafal Doroz & Piotr Porwik

Authors
  1. Krzysztof Wrobel
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  2. Rafal Doroz
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  3. Piotr Porwik
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Corresponding author

Correspondence to Rafal Doroz .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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© 2016 Springer International Publishing Switzerland

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Wrobel, K., Doroz, R., Porwik, P. (2016). Fingerprint Reference Point Detection Based on High Curvature Points. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_55

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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