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Off-line signature verification and forgery detection using fuzzy modeling

Off-line signature verification and forgery detection using fuzzy modeling,10.1016/j.patcog.2004.05.015,Pattern Recognition,Madasu Hanmandlu,Mohd. Haf

Off-line signature verification and forgery detection using fuzzy modeling   (Citations: 24)
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Abstract Automatic signature verification is a well-established and an active area ofresearch with numerous,applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem ofautomatic of f-line signature verification and forgery detection. The proposed,approach is based on fuzzy modeling,that employs,the Takagi–Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds,to a fuzzy set. The features are fuzzified by an exponential membership,function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account ofpossible variations due to handwriting styles and to reflect moods. The membership,functions constitute weights in the TS model. The optimization ofthe output ofthe TS model,with respect to the structural parameters yields the solution f or the parameters. We have also derived two TS models,by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved. Keywords: Off-line signature verification; Forgery detection; Structural parameters; Fuzzy logic; TS model; Bank check recognition
Journal: Pattern Recognition - PR , vol. 38, no. 3, pp. 341-356, 2005
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