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Soft Computing
Published in: Soft Computing 2/2019

19-08-2017 | Methodologies and Application

Quantifying dynamic time warping distance using probabilistic model in verification of dynamic signatures

Authors: Rami Al-Hmouz, Witold Pedrycz, Khaled Daqrouq, Ali Morfeq, Ahmed Al-Hmouz

Published in: Soft Computing | Issue 2/2019

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Abstract

One of the multimodal biometric scenarios is realized by considering several features coming from a single biometric entity. Dynamic signature verification has been utilized considering such scenarios. We present a new approach, namely probabilistic dynamic time warping, to verify dynamic signatures where we use dynamic time warping in realizing distance determination in the verification process. Signatures are segmented into several segments, where probability of each segment is quantified with the aid of a relative distance associated with two selected threshold levels. The final decision is achieved by combining all segment probabilities using a Bayes rule. Experiments demonstrate improvement of equal error rate for the proposed approach for the random forgery. The method has been tested on synthetic dataset and two publicly available databases of dynamic signatures, namely SCV2004 and MCYT100.
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Metadata
Title
Quantifying dynamic time warping distance using probabilistic model in verification of dynamic signatures
Authors
Rami Al-Hmouz
Witold Pedrycz
Khaled Daqrouq
Ali Morfeq
Ahmed Al-Hmouz
Publication date
19-08-2017
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 2/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-017-2782-5

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