The University of Southampton
University of Southampton Institutional Repository

Enhancing off-line biometric signature verification using a fingerprint assessment approach

Enhancing off-line biometric signature verification using a fingerprint assessment approach
Enhancing off-line biometric signature verification using a fingerprint assessment approach
A method designed for matching biometric fingerprint images is applied to the static/image-based ?off-line? human signature modality. Using a publically available signature dataset, the verification performance is compared against three existing static methods. Furthermore, verification is assessed using all four methods within a multi-classifier system. The results show the application of the fingerprint method leads to a comparable performance with existing methods and a significant improvement is achieved within a multi-classifier configuration.
fingerprint recognition, handwriting recognition, educational institutions, Gabor filters, training, biomedical imaging, matched filters
IEEE; Wiley
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Miguel-Hurtado, Oscar
57a8ef90-e39d-4731-a271-0399d7201d34
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Miguel-Hurtado, Oscar
57a8ef90-e39d-4731-a271-0399d7201d34

Guest, Richard and Miguel-Hurtado, Oscar (2011) Enhancing off-line biometric signature verification using a fingerprint assessment approach. In 2011 Carnahan Conference on Security Technology. IEEE; Wiley. 4 pp . (doi:10.1109/CCST.2011.6095883).

Record type: Conference or Workshop Item (Paper)

Abstract

A method designed for matching biometric fingerprint images is applied to the static/image-based ?off-line? human signature modality. Using a publically available signature dataset, the verification performance is compared against three existing static methods. Furthermore, verification is assessed using all four methods within a multi-classifier system. The results show the application of the fingerprint method leads to a comparable performance with existing methods and a significant improvement is achieved within a multi-classifier configuration.

This record has no associated files available for download.

More information

Published date: 18 October 2011
Keywords: fingerprint recognition, handwriting recognition, educational institutions, Gabor filters, training, biomedical imaging, matched filters

Identifiers

Local EPrints ID: 489817
URI: http://eprints.soton.ac.uk/id/eprint/489817
PURE UUID: 2a60bc6a-0609-407a-ad0f-8953910c042b
ORCID for Richard Guest: ORCID iD orcid.org/0000-0001-7535-7336

Catalogue record

Date deposited: 02 May 2024 16:51
Last modified: 03 May 2024 02:07

Export record

Altmetrics

Contributors

Author: Richard Guest ORCID iD
Author: Oscar Miguel-Hurtado

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×