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Title: Handwritten signature verification: Online verification using a fuzzy inference system
Authors: Faruki, M.J. 
Lun, N.Z. 
Ahmed, S.K. 
Issue Date: 2016
Journal: IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings 17 February 2016, Article number 7412195, Pages 232-237 
Abstract: 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.
DOI: 10.1109/ICSIPA.2015.7412195
Appears in Collections:COE Scholarly Publication

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