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Signature verification using a"Siamese" time delay neural network

Bromley, Jane; Bentz, James W.; Bottou, Léon; Guyon, Isabelle; LeCun, Yann; Moore, Cliff; Säckinger, Eduard and Shah, Roopak (1993). Signature verification using a"Siamese" time delay neural network. International Journal of Pattern Recognition and Artificial Intelligence, 7(4) pp. 669–688.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1142/S0218001493000339
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Abstract

This paper describes the development of an algorithm for verification of signatures written on a touch-sensitive pad. The signature verification algorithm is based on an artificial neural network. The novel network presented here, called a “Siamese” time delay neural network, consists of two identical networks joined at their output. During training the network learns to measure the similarity between pairs of signatures. When used for verification, only one half of the Siamese network is evaluated. The output of this half network is the feature vector for the input signature. Verification consists of comparing this feature vector with a stored feature vector for the signer. Signatures closer than a chosen threshold to this stored representation are accepted, all other signatures are rejected as forgeries. System performance is illustrated with experiments performed in the laboratory.

Item Type: Journal Item
Copyright Holders: 1993 World Scientific Publishing
ISSN: 1793-6381
Keywords: dynamic signature verification; artificial neural networks; time delay neural network; touch-sensitive pads
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 35662
Depositing User: Jane M. Bromley
Date Deposited: 22 May 2013 11:27
Last Modified: 08 Dec 2018 17:30
URI: http://oro.open.ac.uk/id/eprint/35662
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