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An Off-line Signature Verification System Based on Fusion of Local and Global Information

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Biometric Authentication (BioAW 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3087))

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Abstract

An off-line signature verification system based on fusion of two machine experts is presented. One of the experts is based on global image analysis and a statistical distance measure while the second one is based on local image analysis and Hidden Markov Models. Experimental results are given on a subcorpus of the large MCYT signature database for random and skilled forgeries. It is shown experimentally that the machine expert based on local information outperforms the system based on global analysis in all reported cases. The two proposed systems are also shown to give complementary recognition information which is exploited with a simple fusion strategy based on the sum rule.

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Author information

Authors and Affiliations

  1. Biometrics Research Lab., ATVS, Universidad Politecnica de Madrid, Spain

    J. Fierrez-Aguilar, N. Alonso-Hermira, G. Moreno-Marquez & J. Ortega-Garcia

Authors
  1. J. Fierrez-Aguilar
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  2. N. Alonso-Hermira
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  3. G. Moreno-Marquez
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  4. J. Ortega-Garcia
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Editor information

Editors and Affiliations

  1. Biometric System Laboratory, DEIS, University of Bologna, via Sacchi 3, 47023, Cesena, Italy

    Davide Maltoni

  2. Department of Computer Science and Engineering, Michigan State University,  

    Anil K. Jain

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© 2004 Springer-Verlag Berlin Heidelberg

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Fierrez-Aguilar, J., Alonso-Hermira, N., Moreno-Marquez, G., Ortega-Garcia, J. (2004). An Off-line Signature Verification System Based on Fusion of Local and Global Information. In: Maltoni, D., Jain, A.K. (eds) Biometric Authentication. BioAW 2004. Lecture Notes in Computer Science, vol 3087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25976-3_27

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  • DOI: https://doi.org/10.1007/978-3-540-25976-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22499-0

  • Online ISBN: 978-3-540-25976-3

  • eBook Packages: Springer Book Archive

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