User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network
Finger-vein biometric identification has gained attention recently due to its several advantages over fingerprint biometric traits. Finger-vein recognition is a method of biometric authentication that applies pattern recognition techniques based on the image of human finger-vein patterns. This pape...
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Asian Research Publishing Network (ARPN)
2016
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Online Access: | http://eprints.utem.edu.my/id/eprint/17278/2/User%20identification%20system%20based%20on%20finger-vein%20pattern%20using%20convolutional%20neural%20network.pdf http://eprints.utem.edu.my/id/eprint/17278/ http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3805.pdf |
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my.utem.eprints.172782021-09-12T23:25:47Z http://eprints.utem.edu.my/id/eprint/17278/ User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network Syazana Itqan, Khalid Syafeeza, Ahmad Radzi Gong, Fook Guan Nur Badariah Ahmad, Mustafa Wong, Yan Chiew M. M., Ibrahim T Technology (General) Finger-vein biometric identification has gained attention recently due to its several advantages over fingerprint biometric traits. Finger-vein recognition is a method of biometric authentication that applies pattern recognition techniques based on the image of human finger-vein patterns. This paper is focused on developing a MATLAB-based finger-vein recognition system using Convolutional Neural Network (CNN) with Graphical User Interface (GUI) as the user input. Two layers of CNN out of the proposed four-layer CNN have been used to retrain the network for new incoming subjects. The pre-processing steps for finger-vein images and CNN design have been conducted pm different platforms. Therefore, this paper discusses the method of linking both parts from different platforms using MEX-files in MATLAB. Evaluation is carried out using images of 50 subjects that are developed in-house. An accuracy of an average of 96% is obtained to recognize 1 to 10 new subjects within less than 10 seconds. Asian Research Publishing Network (ARPN) 2016-03 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/17278/2/User%20identification%20system%20based%20on%20finger-vein%20pattern%20using%20convolutional%20neural%20network.pdf Syazana Itqan, Khalid and Syafeeza, Ahmad Radzi and Gong, Fook Guan and Nur Badariah Ahmad, Mustafa and Wong, Yan Chiew and M. M., Ibrahim (2016) User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network. ARPN Journal Of Engineering And Applied Sciences, 11 (5). pp. 3316-3319. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3805.pdf |
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T Technology (General) Syazana Itqan, Khalid Syafeeza, Ahmad Radzi Gong, Fook Guan Nur Badariah Ahmad, Mustafa Wong, Yan Chiew M. M., Ibrahim User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network |
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Finger-vein biometric identification has gained attention recently due to its several advantages over fingerprint
biometric traits. Finger-vein recognition is a method of biometric authentication that applies pattern recognition techniques based on the image of human finger-vein patterns. This paper is focused on developing a MATLAB-based finger-vein recognition system using Convolutional Neural Network (CNN) with Graphical User Interface (GUI) as the user input. Two layers of CNN out of the proposed four-layer CNN have been used to retrain the network for new incoming subjects. The pre-processing steps for finger-vein images and CNN design have been conducted pm different platforms. Therefore, this paper discusses the method of linking both parts from different platforms using MEX-files in MATLAB. Evaluation is carried out using images of 50 subjects that are developed in-house. An accuracy of an average of 96% is obtained to recognize 1 to 10 new subjects within less than 10 seconds. |
format |
Article |
author |
Syazana Itqan, Khalid Syafeeza, Ahmad Radzi Gong, Fook Guan Nur Badariah Ahmad, Mustafa Wong, Yan Chiew M. M., Ibrahim |
author_facet |
Syazana Itqan, Khalid Syafeeza, Ahmad Radzi Gong, Fook Guan Nur Badariah Ahmad, Mustafa Wong, Yan Chiew M. M., Ibrahim |
author_sort |
Syazana Itqan, Khalid |
title |
User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network |
title_short |
User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network |
title_full |
User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network |
title_fullStr |
User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network |
title_full_unstemmed |
User Identification System Based On Finger-Vein Patterns Using Convolutional Neural Network |
title_sort |
user identification system based on finger-vein patterns using convolutional neural network |
publisher |
Asian Research Publishing Network (ARPN) |
publishDate |
2016 |
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http://eprints.utem.edu.my/id/eprint/17278/2/User%20identification%20system%20based%20on%20finger-vein%20pattern%20using%20convolutional%20neural%20network.pdf http://eprints.utem.edu.my/id/eprint/17278/ http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3805.pdf |
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13.18916 |