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Enhancing static biometric signature verification using Speeded-Up Robust Features

Guest, Richard and Hurtado, Oscar Miguel (2012) Enhancing static biometric signature verification using Speeded-Up Robust Features. In: 2012 IEEE International Carnahan Conference on Security Technology (ICCST). IEEE, pp. 213-217. ISBN 978-1-4673-2450-2. (doi:10.1109/CCST.2012.6393561) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:35814)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/CCST.2012.6393561

Abstract

Automatic biometric static signature verification performs a comparison between signature images (or preformed templates) to verify authenticity. Although widely recognised that performance enhancement can be achieved when using dynamic features, which use temporal/ constructional information, alongside static features, this scenario requires the capture of signatures using specialist sample equipment such a tablet device. The vast majority of (legacy) signatures across a range of important domains, including banking, legal and forensic applications, are in a static format. In this paper we use the Speeded-Up Robust Features (SURF) image registration technique in a novel application to static signature image matching. We use genuine and skilled forgery signatures from the GPDS960 dataset as test data and across a range of enrolment and SURF point distance configurations. The best performance from our method was 11.5% equal error rate by employing a product distance combination of 5 enrolment templates using the lowest 50% of returned registration-point distances. This encouraging result is in line with the current state-of-the-art performance.

Item Type: Book section
DOI/Identification number: 10.1109/CCST.2012.6393561
Uncontrolled keywords: error analysis; feature extraction; robustness; educational institutions; forgery; standards
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: P.S.P. Yapp
Date Deposited: 30 Oct 2013 09:49 UTC
Last Modified: 16 Nov 2021 10:12 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35814 (The current URI for this page, for reference purposes)

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