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Combining Biometric Evidence for Person Authentication

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Advanced Studies in Biometrics

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3161))

Abstract

Humans are excellent experts in person recognition and yet they do not perform excessively well in recognizing others only based on one modality such as single facial image. Experimental evidence of this fact is reported concluding that even human authentication relies on multimodal signal analysis. The elements of automatic multimodal authentication along with system models are then presented. These include the machine experts as well as machine supervisors. In particular, fingerprint and speech based systems will serve as illustration. A signal adaptive supervisor based on the input biometric signal quality is evaluated. Experimental results on data collected from a mobile telephone prototype application are reported demonstrating the benefits of the reported scheme.

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Author information

Authors and Affiliations

  1. Halmstad University, Sweden

    J. Bigun

  2. Universidad Politecnica de Madrid, Spain

    J. Fierrez-Aguilar, J. Ortega-Garcia & J. Gonzalez-Rodriguez

Authors
  1. J. Bigun
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  2. J. Fierrez-Aguilar
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  3. J. Ortega-Garcia
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  4. J. Gonzalez-Rodriguez
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Editor information

Editors and Affiliations

  1. University of Sassari, 07041, Alghero, Italy

    Massimo Tistarelli

  2. School of Information Science, Computer and Electrical Engineering (IDE), Halmstad University, Box 823, SE-301 18, Halmstad

    Josef Bigun

  3. DEIR - University of Sassari, Sassari, Italy

    Enrico Grosso

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© 2005 Springer-Verlag Berlin Heidelberg

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Bigun, J., Fierrez-Aguilar, J., Ortega-Garcia, J., Gonzalez-Rodriguez, J. (2005). Combining Biometric Evidence for Person Authentication. In: Tistarelli, M., Bigun, J., Grosso, E. (eds) Advanced Studies in Biometrics. Lecture Notes in Computer Science, vol 3161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11493648_1

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  • DOI: https://doi.org/10.1007/11493648_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26204-6

  • Online ISBN: 978-3-540-28638-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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