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Learning Strategies for Knowledge-Base Updating in Online Signature Verification Systems

  • Giuseppe Pirlo
  • Donato Impedovo
  • Donato Barbuzzi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8158)

Abstract

Updating of reference information is a crucial task for automatic signature verification. In fact, signature characteristics vary in time and whatever approach is considered the effectiveness of a signature verification system strongly depends on the extent to which reference information is able to model the changeable characteristics of users’ signatures. This paper addresses the problem of knowledge-base updating in multi-expert signature verification systems and introduces a new strategy which exploits the collective behavior of classifiers to select the most profitable samples for knowledge-base updating. The experimental tests, carried out using the SUSig database, demonstrate the effectiveness of the new strategy.

Keywords

Signature Verification Feedback-based Strategy Multi Expert System 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Giuseppe Pirlo
    • 1
  • Donato Impedovo
    • 2
  • Donato Barbuzzi
    • 1
  1. 1.Department of Computer ScienceUniversity of BariBariItaly
  2. 2.Department of Electrical and Electronic EngineeringPolytechnic of BariBariItaly

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