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On Hunting Animals of the Biometric Menagerie for Online Signature
Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concep...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824397/ https://www.ncbi.nlm.nih.gov/pubmed/27054836 http://dx.doi.org/10.1371/journal.pone.0151691 |
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author | Houmani, Nesma Garcia-Salicetti, Sonia |
author_facet | Houmani, Nesma Garcia-Salicetti, Sonia |
author_sort | Houmani, Nesma |
collection | PubMed |
description | Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving automatically writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database. |
format | Online Article Text |
id | pubmed-4824397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48243972016-04-22 On Hunting Animals of the Biometric Menagerie for Online Signature Houmani, Nesma Garcia-Salicetti, Sonia PLoS One Research Article Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving automatically writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database. Public Library of Science 2016-04-07 /pmc/articles/PMC4824397/ /pubmed/27054836 http://dx.doi.org/10.1371/journal.pone.0151691 Text en © 2016 Houmani, Garcia-Salicetti http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Houmani, Nesma Garcia-Salicetti, Sonia On Hunting Animals of the Biometric Menagerie for Online Signature |
title | On Hunting Animals of the Biometric Menagerie for Online Signature |
title_full | On Hunting Animals of the Biometric Menagerie for Online Signature |
title_fullStr | On Hunting Animals of the Biometric Menagerie for Online Signature |
title_full_unstemmed | On Hunting Animals of the Biometric Menagerie for Online Signature |
title_short | On Hunting Animals of the Biometric Menagerie for Online Signature |
title_sort | on hunting animals of the biometric menagerie for online signature |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4824397/ https://www.ncbi.nlm.nih.gov/pubmed/27054836 http://dx.doi.org/10.1371/journal.pone.0151691 |
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