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Quality Measures for Online Handwritten Signatures

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Signal and Image Processing for Biometrics

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 292))

Abstract

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.

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Author information

Authors and Affiliations

  1. Laboratoire SIGMA, ESPCI ParisTech, 10 rue Vauquelin, 75005, Paris, France

    Nesma Houmani

  2. CNRS UMR 5157 SAMOVAR, CEA Saclay Nano-Innov, Institut Mines-Telecom/Télécom SudParis, PC176 Bât. 861, 91191, Gif sur Yvette Cedex, France

    Sonia Garcia-Salicetti

Authors
  1. Nesma Houmani
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  2. Sonia Garcia-Salicetti
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Corresponding authors

Correspondence to Nesma Houmani or Sonia Garcia-Salicetti .

Editor information

Editors and Affiliations

  1. Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Jacob Scharcanski

  2. IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal

    Hugo Proença

  3. Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA

    Eliza Du

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Houmani, N., Garcia-Salicetti, S. (2014). Quality Measures for Online Handwritten Signatures. In: Scharcanski, J., Proença, H., Du, E. (eds) Signal and Image Processing for Biometrics. Lecture Notes in Electrical Engineering, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54080-6_10

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  • DOI: https://doi.org/10.1007/978-3-642-54080-6_10

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  • Print ISBN: 978-3-642-54079-0

  • Online ISBN: 978-3-642-54080-6

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