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Ensemble-Based Methods for Cancellable Biometrics

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Artificial Neural Networks – ICANN 2010 (ICANN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6352))

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Abstract

In this paper, we investigate the use of genetic algorithms and ensemble systems in cancellable biometrics, using fingerprint-based identification to illustrate the possible benefits accruing. The main aim is to analyze the performance of these well-established structures on transformed biometric data to determine whether they have a positive effect on the performance of this complex and difficult task.

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References

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Author information

Authors and Affiliations

  1. Dep of Informatics and Applied Mathematics, Federal University of RN, Natal, Brazil

    Anne Canuto, Laura E. A Santana, Fernando Pintro & Antonino Feitosa Neto

  2. School of Engineering and Digital Arts, University of Kent, Canterbury, UK

    Michael Fairhurst

Authors
  1. Anne Canuto
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  2. Michael Fairhurst
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  3. Laura E. A Santana
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  4. Fernando Pintro
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  5. Antonino Feitosa Neto
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Editor information

Editors and Affiliations

  1. Department of Informatics, TEI of Thessaloniki, 57400, Sindos, Greece

    Konstantinos Diamantaras

  2. School of Physics, Astronomy, and Informatics, Department of Informatics, Nicolaus Copernicus University, ul. Grudziadzka 5, 87-100, Torun, Poland

    Wlodek Duch

  3. Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, Pantazidou 193, 68200, Orestiada, Thrace, Greece

    Lazaros S. Iliadis

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© 2010 Springer-Verlag Berlin Heidelberg

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Canuto, A., Fairhurst, M., Santana, L.E.A., Pintro, F., Neto, A.F. (2010). Ensemble-Based Methods for Cancellable Biometrics. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15819-3_55

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  • DOI: https://doi.org/10.1007/978-3-642-15819-3_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15818-6

  • Online ISBN: 978-3-642-15819-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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