Quality Measures for Online Handwritten Signatures

  • Nesma Houmani
  • Sonia Garcia-Salicetti
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 292)


This chapter tackles the problem of quality of online signature samples. Several works in the literature point out signature complexity and signature stability as main quality criteria for this behavioral biometric modality. The drawback of these works is the measurement of such criteria separately. In this study, we propose to analyze such criteria with a different unifying view, in terms of entropy-based measures. We consider signature complexity as the intrinsic disorder of a signature instance and variability as the intra-class disorder of a set of genuine signatures. We introduce a novel statistical measure of complexity for signature samples and analyze it relatively to Personal Entropy that we proposed in former works. We study the power of both measures for an automatic writer categorization on several databases. We show that such categories retrieve separately on one hand degraded data and on the other hand good quality signatures. Finally, the degradation of signatures due to mobile acquisition conditions is quantified by our entropy-based measures.


Signature complexity Signature variability Entropy Hierarchical clustering Hidden Markov Models Writer categories Online signature verification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Laboratoire SIGMAESPCI ParisTechParisFrance
  2. 2.CNRS UMR 5157 SAMOVAR, CEA Saclay Nano-InnovInstitut Mines-Telecom/Télécom SudParisGif sur Yvette CedexFrance

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