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New Finger Biometric Method Using Near Infrared Imaging

In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified Gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images...

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Detalles Bibliográficos
Autores principales: Lee, Eui Chul, Jung, Hyunwoo, Kim, Daeyeoul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231585/
https://www.ncbi.nlm.nih.gov/pubmed/22163741
http://dx.doi.org/10.3390/s110302319
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author Lee, Eui Chul
Jung, Hyunwoo
Kim, Daeyeoul
author_facet Lee, Eui Chul
Jung, Hyunwoo
Kim, Daeyeoul
author_sort Lee, Eui Chul
collection PubMed
description In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified Gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting each feature using different methods, the modified Gaussian high-pass filter is fully convolved. Therefore, the extracted binary patterns of finger images include the multimodal features of veins and finger geometries. Experimental results show that the proposed method has an error rate of 0.13%.
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spelling pubmed-32315852011-12-07 New Finger Biometric Method Using Near Infrared Imaging Lee, Eui Chul Jung, Hyunwoo Kim, Daeyeoul Sensors (Basel) Article In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified Gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting each feature using different methods, the modified Gaussian high-pass filter is fully convolved. Therefore, the extracted binary patterns of finger images include the multimodal features of veins and finger geometries. Experimental results show that the proposed method has an error rate of 0.13%. Molecular Diversity Preservation International (MDPI) 2011-02-24 /pmc/articles/PMC3231585/ /pubmed/22163741 http://dx.doi.org/10.3390/s110302319 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Lee, Eui Chul
Jung, Hyunwoo
Kim, Daeyeoul
New Finger Biometric Method Using Near Infrared Imaging
title New Finger Biometric Method Using Near Infrared Imaging
title_full New Finger Biometric Method Using Near Infrared Imaging
title_fullStr New Finger Biometric Method Using Near Infrared Imaging
title_full_unstemmed New Finger Biometric Method Using Near Infrared Imaging
title_short New Finger Biometric Method Using Near Infrared Imaging
title_sort new finger biometric method using near infrared imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231585/
https://www.ncbi.nlm.nih.gov/pubmed/22163741
http://dx.doi.org/10.3390/s110302319
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