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Handwritten signature verification: Online verification using a fuzzy inference system

Biometric features posses the significant advantage of being difficult to lose, forget or duplicate. Hence, a FIS-based method is used for signature verification. FIS is well suited for this task due to the similarity between an individual signatures with subtle differences between each signature sa...

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Main Authors: Faruki, M.J., Lun, N.Z., Ahmed, S.K.
Format: Conference Paper
Language:English
Published: 2017
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spelling my.uniten.dspace-50052017-11-14T03:39:52Z Handwritten signature verification: Online verification using a fuzzy inference system Faruki, M.J. Lun, N.Z. Ahmed, S.K. Biometric features posses the significant advantage of being difficult to lose, forget or duplicate. Hence, a FIS-based method is used for signature verification. FIS is well suited for this task due to the similarity between an individual signatures with subtle differences between each signature sample. Signature samples are collected using a tablet PC. The individuals draw their signatures usinga pressure sensitive pen on the tablet. Eight dynamic features are extracted from the signature data. These eight features are then fuzzified for training of a FIS. The system is then used to determine whether the signature is genuine or forged. A False Acceptance Rate (FAR) of 10.67% and a False Rejection Rate (FRR) of 8.0% demonstrate the promise of this system. © 2015 IEEE. 2017-11-14T03:21:13Z 2017-11-14T03:21:13Z 2016 Conference Paper 10.1109/ICSIPA.2015.7412195 en IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings 17 February 2016, Article number 7412195, Pages 232-237
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description Biometric features posses the significant advantage of being difficult to lose, forget or duplicate. Hence, a FIS-based method is used for signature verification. FIS is well suited for this task due to the similarity between an individual signatures with subtle differences between each signature sample. Signature samples are collected using a tablet PC. The individuals draw their signatures usinga pressure sensitive pen on the tablet. Eight dynamic features are extracted from the signature data. These eight features are then fuzzified for training of a FIS. The system is then used to determine whether the signature is genuine or forged. A False Acceptance Rate (FAR) of 10.67% and a False Rejection Rate (FRR) of 8.0% demonstrate the promise of this system. © 2015 IEEE.
format Conference Paper
author Faruki, M.J.
Lun, N.Z.
Ahmed, S.K.
spellingShingle Faruki, M.J.
Lun, N.Z.
Ahmed, S.K.
Handwritten signature verification: Online verification using a fuzzy inference system
author_facet Faruki, M.J.
Lun, N.Z.
Ahmed, S.K.
author_sort Faruki, M.J.
title Handwritten signature verification: Online verification using a fuzzy inference system
title_short Handwritten signature verification: Online verification using a fuzzy inference system
title_full Handwritten signature verification: Online verification using a fuzzy inference system
title_fullStr Handwritten signature verification: Online verification using a fuzzy inference system
title_full_unstemmed Handwritten signature verification: Online verification using a fuzzy inference system
title_sort handwritten signature verification: online verification using a fuzzy inference system
publishDate 2017
_version_ 1644493587951386624
score 13.214268

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