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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2013: Artificial Intelligence and Soft Computing pp 113–121Cite as

New Algorithm for Evolutionary Selection of the Dynamic Signature Global Features

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7895))

Abstract

Methods using dynamic signature for identity verification may be divided into three main categories: global methods, local function based methods and regional function based methods. Global methods base on a set of global parametric features, which are extracted from signature of user. Global feature extraction methods have been often presented in the literature. Another interesting task is selection of a features group which will be considered individually for each user during training and verification process. In this paper we propose a new approach to automatic evolutionary selection of the dynamic signature global features. Our method was tested with use of the SVC2004 public on-line signature database.

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Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Częstochowa University of Technology, Poland

    Marcin Zalasiński, Krystian Łapa & Krzysztof Cpałka

Authors
  1. Marcin Zalasiński
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  2. Krystian Łapa
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  3. Krzysztof Cpałka
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Michiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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Zalasiński, M., Łapa, K., Cpałka, K. (2013). New Algorithm for Evolutionary Selection of the Dynamic Signature Global Features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7895. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38610-7_11

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  • DOI: https://doi.org/10.1007/978-3-642-38610-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38609-1

  • Online ISBN: 978-3-642-38610-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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