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
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Miguel-Hurtado, Oscar
57a8ef90-e39d-4731-a271-0399d7201d34
18 October 2011
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.
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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
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Date deposited: 02 May 2024 16:51
Last modified: 03 May 2024 02:07
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Contributors
Author:
Richard Guest
Author:
Oscar Miguel-Hurtado
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