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Comparing Elastic Alignment Algorithms for the Off-Line Signature Verification Problem

  • J. F. Vélez
  • A. Sánchez
  • A. B. Moreno
  • L. Morillo-Velarde
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6687)

Abstract

This paper systematically compares two elastic graph matching methods for off-line signature verification: shape-memory snakes and parallel segment matching, respectively. As in many practical applications (i.e. those related to bank environments), the number of sample signatures to train the system must be very reduced, we selected these two methods which hold that property. Both methods also share some other similarities since they use graph models to perform the verification task and require a registration pre-processing. Experimental results on the same database and using the same evaluation metrics have shown that the shape-memory snakes clearly outperformed to the parallel segment matching approach on the same signature dataset (9% EER compared to 24% EER, respectively).

Keywords

off-line signature verification snakes graph matching elastic alignment pattern recognition fuzzy sets. 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • J. F. Vélez
    • 1
  • A. Sánchez
    • 1
  • A. B. Moreno
    • 1
  • L. Morillo-Velarde
    • 2
  1. 1.Departamento de Ciencias de la ComputaciónUniversidad Rey Juan CarlosMóstoles (Madrid)Spain
  2. 2.Investigación y Programas, S.A.MadridSpain

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