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Online signature verification with neural networks classifier and fuzzy inference

Khalid, Marzuki and Mokayed, Hamam and Yusof, Rubiyah and Ono, Osamu (2009) Online signature verification with neural networks classifier and fuzzy inference. In: Proceedings - 2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009. Institute of Electrical and Electronics Engineers, New York, pp. 236-241. ISBN 978-076953648-4

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Official URL: http://dx.doi.org/10.1109/AMS.2009.23

Abstract

Compared to physiologically based biometric systems such as fingerprint, face, palm-vein and retina, behavioral based biometric systems such as signature, voice, gait, etc. are less popular and many are still in their infancy. A major problem is due to inconsistencies in human behavior which require more robust algorithms in their developments. In this paper, an online signature verification system is proposed based on neural networks classifier and fuzzy inference. The software has been developed with a robust validation module based on Pearson's correlation algorithm in which more consistent sets of user's signature are enrolled. In this way, more consistent sets of training patterns are used to train the neural network modules based on the popular backpropagation algorithm. To increase the robustness not only the neural network threshold is used for the verification, the time and length of the signature are also calculated. A fuzzy inference module is then set up to infer the three thresholds for human-like decision outputs. The signature verification system shows better consistency and is more robust than previous designs.

Item Type:Book Section
Additional Information:2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009; Bandung, Bali; 25 May 2009 through 26 May 2009
Uncontrolled Keywords:biometric systems, consistent sets, correlation algorithm, human behaviors, module-based; neural networks classifiers, on-line signature verification, on-line signature verification system, robust algorithm, signature verification, training patterns
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:13029
Deposited By: Mrs Liza Porijo
Deposited On:14 Jul 2011 01:25
Last Modified:14 Jul 2011 01:25

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