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Learning Local Correspondences for Static Signature Verification

  • G. Pirlo
  • D. Impedovo
  • E. Stasolla
  • C. A. Trullo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5883)

Abstract

This paper presents a new approach for off-line signature verification. Signature verification is performed by matching only well-selected regions of the signature images. More precisely, from the analysis of lower and upper contours of a signature image, region stability is estimated and the most stable regions are selected for verification, during the enrollment phase. In the verification phase, an unknown specimen is verified through the analysis of the selected regions, on the basis of a well-defined similarity measure. The experimental results, carried out on signatures from the GPDS database, demonstrate the potential of the proposed approach.

Keywords

Signature Image Enrollment Phase Handwriting Recognition False Acceptance Rate False Rejection Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • G. Pirlo
    • 1
    • 3
  • D. Impedovo
    • 2
    • 3
  • E. Stasolla
    • 1
    • 3
  • C. A. Trullo
    • 1
    • 3
  1. 1.Dipartimento di InformaticaUniversità degli Studi di BariBari
  2. 2.Dip. di Ing. Elettrotecnica ed ElettronicaPolitecnico di BariBari
  3. 3.Centro “Rete Puglia”Università degli Studi di BariBari

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