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The Method of Predicting Changes of a Dynamic Signature Using Possibilities of Population-Based Algorithms

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11508))

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Abstract

Verification of a signature on the basis of its dynamics is an important issue of biometrics. This kind signature is called the dynamic signature. It can be represented, among others, by the set of features determined on the basis of time characteristics: pen velocity, pen pressure on the surface of a graphics tablet, etc. Values of the features can change over time, individually for each signer. Our previous research was related to the prediction of these changes to increase the effectiveness of a signature verification process. This approach was effective. The main purpose of this work is to compare the effectiveness of the methods for a prediction of signature features changes using selected population-based algorithms. They are used for learning of the fuzzy system used for prediction. Tests of the proposed approach were performed using ATVS-SLT DB database of the dynamic signatures.

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Author information

Authors and Affiliations

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

    Marcin Zalasiński, Krystian Łapa & Krzysztof Cpałka

  2. Information Technology Institute, University of Social Sciences, 90-113, Łodź, Poland

    Alina Marchlewska

  3. Clark University, Worcester, MA, 01610, USA

    Alina Marchlewska

Authors
  1. Marcin Zalasiński
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  2. Krystian Łapa
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  3. Krzysztof Cpałka
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  4. Alina Marchlewska
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Corresponding author

Correspondence to Marcin Zalasiński .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Zalasiński, M., Łapa, K., Cpałka, K., Marchlewska, A. (2019). The Method of Predicting Changes of a Dynamic Signature Using Possibilities of Population-Based Algorithms. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11508. Springer, Cham. https://doi.org/10.1007/978-3-030-20912-4_49

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  • DOI: https://doi.org/10.1007/978-3-030-20912-4_49

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