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Universal Forgery Features Idea: A Solution for User–Adjusted Threshold in Signature Verification

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Transactions on Computational Collective Intelligence IX

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 7770))

Abstract

Handwritten signature verification algorithms are designed to distinguish between genuine signatures and forgeries. One of the central issues with such algorithms is the unavailability of skilled forgeries during the template creation. As a solution, we propose the idea of universal forgery features, where a global classifier is used to classify a signature as a genuine one or as a forgery, without the actual knowledge of the signature template and its owner. This classifier is trained once, during the system tuning on a group of historical data. A global classifier trained on a set of training signatures is not to be additionally trained after implementation; in other words, additional user enrollments have no effect on the global classifier parameters. This idea effectively solves the issue of the lack of skilled forgeries during template creation. We show that this approach can be applied both in on-line and off-line signature verification systems.

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Authors and Affiliations

  1. Research and Academic Computer Network NASK, Wawozowa 18, 02796, Warsaw, Poland

    Joanna Putz-Leszczynska & Andrzej Pacut

  2. Warsaw University of Technology, Nowowiejska 15/19, 00663, Warsaw, Poland

    Joanna Putz-Leszczynska & Andrzej Pacut

Authors
  1. Joanna Putz-Leszczynska
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  2. Andrzej Pacut
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Editors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Str. Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen

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Putz-Leszczynska, J., Pacut, A. (2013). Universal Forgery Features Idea: A Solution for User–Adjusted Threshold in Signature Verification. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence IX. Lecture Notes in Computer Science, vol 7770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36815-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-36815-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36814-1

  • Online ISBN: 978-3-642-36815-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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