Palm Vein Recognition System Based on Derived Pattern and Feature Vectors

International Journal of Digital Literacy and Digital Competence Volume 8 • Issue 2 • April-June 2017

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Principais autores: Lawal, A, Aina, S, Okegbile, S, Ayeni, S, Omole, D, Adeniran, O
Formato: Periódico
Idioma:en_US
Publicado em: IGI Global 2020
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Acesso em linha:https://ir.oauife.edu.ng/handle/123456789/5158
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author Lawal, A
Aina, S
Okegbile, S
Ayeni, S
Omole, D
Adeniran, O
author_facet Lawal, A
Aina, S
Okegbile, S
Ayeni, S
Omole, D
Adeniran, O
author_sort Lawal, A
collection DSpace
description International Journal of Digital Literacy and Digital Competence Volume 8 • Issue 2 • April-June 2017
format Journal
id oai:ir.oauife.edu.ng:123456789-5158
institution My University
language en_US
publishDate 2020
publisher IGI Global
record_format dspace
spelling oai:ir.oauife.edu.ng:123456789-51582023-05-13T11:12:26Z Palm Vein Recognition System Based on Derived Pattern and Feature Vectors Lawal, A Aina, S Okegbile, S Ayeni, S Omole, D Adeniran, O Biometric, CASIA Palm Veins Pattern Matching thinning International Journal of Digital Literacy and Digital Competence Volume 8 • Issue 2 • April-June 2017 Biometrics is a technology for recognition under which Palm vein recognition stems. They are of crucial importance in various applications of high sensitivity. This article develops a palm vein recognition model, based on derived pattern and feature vectors. All the palm print images used in this work were obtained from CASIA Multi-Spectral Palmprint Image Database V1.0 (CASIA database). First, a Region of Interest (ROI) was identified and extracted from the palm print images. Next, Histogram Equalization was used to enhance the area of the palm print image in the Region of Interest. The enhanced image obtained was subjected to the Zhang Suen's Thinning Algorithm to extract appropriate features in the palm print images needed for authentication. The features derived based on this vascular pattern thinning algorithm which are then compared and evaluated to carry out ‘matching'. The Pattern Matching itself was done using the Euclidean Distance for subsequent matching. The model was designed using UML, and implemented with C# and MS SQL on Microsoft Visual Studio platform. The developed system was evaluated based on False Acceptance, False Rejection and Equal Error Rate (EER) values obtained from the system. The results of testing and evaluation show that the developed system has achieved high recognition accuracy. 2020-02-07T13:07:23Z 2020-02-07T13:07:23Z 2017-04 Journal https://ir.oauife.edu.ng/handle/123456789/5158 en_US application/pdf IGI Global
spellingShingle Biometric,
CASIA
Palm Veins
Pattern Matching
thinning
Lawal, A
Aina, S
Okegbile, S
Ayeni, S
Omole, D
Adeniran, O
Palm Vein Recognition System Based on Derived Pattern and Feature Vectors
title Palm Vein Recognition System Based on Derived Pattern and Feature Vectors
title_full Palm Vein Recognition System Based on Derived Pattern and Feature Vectors
title_fullStr Palm Vein Recognition System Based on Derived Pattern and Feature Vectors
title_full_unstemmed Palm Vein Recognition System Based on Derived Pattern and Feature Vectors
title_short Palm Vein Recognition System Based on Derived Pattern and Feature Vectors
title_sort palm vein recognition system based on derived pattern and feature vectors
topic Biometric,
CASIA
Palm Veins
Pattern Matching
thinning
url https://ir.oauife.edu.ng/handle/123456789/5158
work_keys_str_mv AT lawala palmveinrecognitionsystembasedonderivedpatternandfeaturevectors
AT ainas palmveinrecognitionsystembasedonderivedpatternandfeaturevectors
AT okegbiles palmveinrecognitionsystembasedonderivedpatternandfeaturevectors
AT ayenis palmveinrecognitionsystembasedonderivedpatternandfeaturevectors
AT omoled palmveinrecognitionsystembasedonderivedpatternandfeaturevectors
AT adenirano palmveinrecognitionsystembasedonderivedpatternandfeaturevectors