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Impact of signature legibility and signature type in off-line signature verification
Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain. (ATVS/Biometric Recognition Group)ORCID iD: 0000-0002-1400-346X
University of Kent, UK.
Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain. (ATVS/Biometric Recognition Group)
Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain. (ATVS/Biometric Recognition Group)
2007 (English)In: Biometrics Symposium, 2007: [Baltimore, Maryland]: 11-13 Sept. 2007, Piscataway, N.J.: IEEE Press, 2007, Vol. 1, 1-6 p.Conference paper, Published paper (Refereed)
Abstract [en]

The performance of two popular approaches for off-line signature nature verification in terms of signature legibility and signature type is studied. We investigate experimentally if the knowledge of letters, syllables or name instances can help in the process of imitating a signature. Experimental results are given on a sub-corpus of the MCYT signature database for random and skilled forgeries. We use for our experiments two machine experts, one based on global image analysis and statistical distance measures, and the second based on local image analysis and Hidden Markov Models. Verification results are reported in terms of Equal Error Rate (EER), False Acceptance Rate (FAR) and False Rejection Rate (FRR). ©2007 IEEE.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2007. Vol. 1, 1-6 p.
Keyword [en]
Biometrics, Error analysis, Image analysis, Imaging techniques, Learning systems, Markov processes, Speech recognition
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-21200DOI: 10.1109/BCC.2007.4430548ISI: 000255188600020Scopus ID: 2-s2.0-50249148484ISBN: 978-142441549-6 OAI: oai:DiVA.org:hh-21200DiVA: diva2:589333
Conference
Proc. IEEE Biometrics Symposium, BSYM, Baltimore, USA, 11-13 September, 2007
Available from: 2013-01-17 Created: 2013-01-16 Last updated: 2015-09-29Bibliographically approved

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Alonso-Fernandez, Fernando
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CiteExportLink to record
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