Generation and Evaluation of Brute-Force Signature Forgeries

  • Alain Wahl
  • Jean Hennebert
  • Andreas Humm
  • Rolf Ingold
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4105)


We present a procedure to create brute-force signature forgeries. The procedure is supported by Sign4J, a dynamic signature imitation training software that was specifically built to help people learn to imitate the dynamics of signatures. The main novelty of the procedure lies in a feedback mechanism that is provided to let the user know how good the imitation is and on what part of the signature the user has still to improve. The procedure and the software are used to generate a set of brute-force signatures on the MCYT-100 database. This set of forged signatures is used to evaluate the rejection performance of a baseline dynamic signature verification system. As expected, the brute-force forgeries generate more false acceptation in comparison to the random and low-force forgeries available in the MCYT-100 database.


Gaussian Mixture Model Original Signature Equal Error Rate Dynamic Signature Local Threshold 
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 2006

Authors and Affiliations

  • Alain Wahl
    • 1
  • Jean Hennebert
    • 1
  • Andreas Humm
    • 1
  • Rolf Ingold
    • 1
  1. 1.Université de FribourgFribourgSwitzerland

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