Johnson, Emma and Guest, Richard (2011) The Use of Static Biometric Signature Data from Public Service Forms. In: Biometrics and ID Management COST 2101 European Workshop. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 73-82. ISBN 978-3-642-19529-7. E-ISBN 978-3-642-19530-3. (doi:10.1007/978-3-642-19530-3_7) (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:27596)
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/10.1007/978-3-642-19530-3_7 |
Abstract
Automatic signature verification/recognition is a commonly used form of biometric authentication. Signatures are typically provided for legal purposes on public service application forms but not used for subsequent biometric recognition. This paper investigates a number of factors concerning the use of signatures in so-called static form (an image of a completed signature) to enable the sample to be used as stand-alone or supplementary data alongside other biometric modalities. Specifically we investigate common sizes of unconstrained signatures within a population, assess the size of application form signing areas with respect to potential constraints and finally investigate performance issues of how constrained and unconstrained enrolment signature data from forms can be accurately matched against constrained and unconstrained verification data, representing the full range of usage scenarios. The study identifies that accuracy can be maintained when constrained signatures data is verified against other constrained samples while the best performance occurs when unconstrained signatures are used for both enrolment and verification.
Item Type: | Book section |
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DOI/Identification number: | 10.1007/978-3-642-19530-3_7 |
Uncontrolled keywords: | signature biometrics; static feature analysis; form design |
Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | J. Harries |
Date Deposited: | 25 Mar 2011 15:29 UTC |
Last Modified: | 05 Nov 2024 10:08 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/27596 (The current URI for this page, for reference purposes) |
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