Loading…

FPGA-based embedded hand vein biometric authentication system

Biometric authentication provides a high security and reliable approach to be used in security access system. However, this authentication method has not been widely implemented in a resource-constrained embedded system. In this project, we investigate a method of personal authentication based on in...

Full description

Saved in:
Bibliographic Details
Main Authors: Eng, P.C., Khalil-Hani, M.
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 5
container_issue
container_start_page 1
container_title
container_volume
creator Eng, P.C.
Khalil-Hani, M.
description Biometric authentication provides a high security and reliable approach to be used in security access system. However, this authentication method has not been widely implemented in a resource-constrained embedded system. In this project, we investigate a method of personal authentication based on infrared vein pattern in the back of the hand, targeted for embedded system which is implemented in Altera Nios II FPGA prototyping system, running on Real Time Operating System (RTOS). The RTOS applied is Nios2-Linux. A biometric feature is extracted from the vein pattern image and then matched for personal authentication. The algorithm consists of four modules: image capturing, image pre-processing, feature extraction, and the authentication module. These image processing algorithms executed in an embedded system with a 50 MHz fixed point processor. Preliminary experiment on a database of 82 images of 15 candidates show promising result with the system reaching equal error rate of 5.5%.
doi_str_mv 10.1109/TENCON.2009.5396173
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_5396173</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5396173</ieee_id><sourcerecordid>5396173</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-740505aae1284925f51901f302d76695550e3f8fe74d1f1a6473926f4053dfab3</originalsourceid><addsrcrecordid>eNo9UM1qwkAY3P4IVZsn8JIXiP32P9-hBwlqC6I95C4b91vc0sSSpAXfvinazmUGhpmBYWzGYc454FO53Ba77VwA4FxLNNzKGzbhSiiltLL2lo0F15hJpeGOJWjzP8-I-39PiRGb_HYgSAT1wJKue4cBGiygGLPn1dt6kVWuI59SXZH3gzi6xqffFJu0iqea-jYeUvfVH6np48H18dSk3bnrqX5ko-A-OkquPGXlalkWL9lmt34tFpssIvSZVcOcdo64yBUKHTRH4EGC8NYY1FoDyZAHssrzwJ1RVqIwYYhJH1wlp2x2qY1EtP9sY-3a8_76ivwBQPZOHQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>FPGA-based embedded hand vein biometric authentication system</title><source>IEEE Xplore All Conference Series</source><creator>Eng, P.C. ; Khalil-Hani, M.</creator><creatorcontrib>Eng, P.C. ; Khalil-Hani, M.</creatorcontrib><description>Biometric authentication provides a high security and reliable approach to be used in security access system. However, this authentication method has not been widely implemented in a resource-constrained embedded system. In this project, we investigate a method of personal authentication based on infrared vein pattern in the back of the hand, targeted for embedded system which is implemented in Altera Nios II FPGA prototyping system, running on Real Time Operating System (RTOS). The RTOS applied is Nios2-Linux. A biometric feature is extracted from the vein pattern image and then matched for personal authentication. The algorithm consists of four modules: image capturing, image pre-processing, feature extraction, and the authentication module. These image processing algorithms executed in an embedded system with a 50 MHz fixed point processor. Preliminary experiment on a database of 82 images of 15 candidates show promising result with the system reaching equal error rate of 5.5%.</description><identifier>ISSN: 2159-3442</identifier><identifier>ISBN: 9781424445462</identifier><identifier>ISBN: 1424445469</identifier><identifier>EISSN: 2159-3450</identifier><identifier>EISBN: 1424445477</identifier><identifier>EISBN: 9781424445479</identifier><identifier>DOI: 10.1109/TENCON.2009.5396173</identifier><identifier>LCCN: 2009903904</identifier><language>eng</language><publisher>IEEE</publisher><subject>Authentication ; Biometric ; Biometrics ; Embedded system ; Feature extraction ; Field programmable gate arrays ; FPGA ; Hand Vein ; Nios2-linu ; Operating systems ; Prototypes ; Real time systems ; RTOS ; Security ; Veins</subject><ispartof>TENCON 2009 - 2009 IEEE Region 10 Conference, 2009, p.1-5</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5396173$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2057,27924,54554,54919,54931</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5396173$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Eng, P.C.</creatorcontrib><creatorcontrib>Khalil-Hani, M.</creatorcontrib><title>FPGA-based embedded hand vein biometric authentication system</title><title>TENCON 2009 - 2009 IEEE Region 10 Conference</title><addtitle>TENCON</addtitle><description>Biometric authentication provides a high security and reliable approach to be used in security access system. However, this authentication method has not been widely implemented in a resource-constrained embedded system. In this project, we investigate a method of personal authentication based on infrared vein pattern in the back of the hand, targeted for embedded system which is implemented in Altera Nios II FPGA prototyping system, running on Real Time Operating System (RTOS). The RTOS applied is Nios2-Linux. A biometric feature is extracted from the vein pattern image and then matched for personal authentication. The algorithm consists of four modules: image capturing, image pre-processing, feature extraction, and the authentication module. These image processing algorithms executed in an embedded system with a 50 MHz fixed point processor. Preliminary experiment on a database of 82 images of 15 candidates show promising result with the system reaching equal error rate of 5.5%.</description><subject>Authentication</subject><subject>Biometric</subject><subject>Biometrics</subject><subject>Embedded system</subject><subject>Feature extraction</subject><subject>Field programmable gate arrays</subject><subject>FPGA</subject><subject>Hand Vein</subject><subject>Nios2-linu</subject><subject>Operating systems</subject><subject>Prototypes</subject><subject>Real time systems</subject><subject>RTOS</subject><subject>Security</subject><subject>Veins</subject><issn>2159-3442</issn><issn>2159-3450</issn><isbn>9781424445462</isbn><isbn>1424445469</isbn><isbn>1424445477</isbn><isbn>9781424445479</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo9UM1qwkAY3P4IVZsn8JIXiP32P9-hBwlqC6I95C4b91vc0sSSpAXfvinazmUGhpmBYWzGYc454FO53Ba77VwA4FxLNNzKGzbhSiiltLL2lo0F15hJpeGOJWjzP8-I-39PiRGb_HYgSAT1wJKue4cBGiygGLPn1dt6kVWuI59SXZH3gzi6xqffFJu0iqea-jYeUvfVH6np48H18dSk3bnrqX5ko-A-OkquPGXlalkWL9lmt34tFpssIvSZVcOcdo64yBUKHTRH4EGC8NYY1FoDyZAHssrzwJ1RVqIwYYhJH1wlp2x2qY1EtP9sY-3a8_76ivwBQPZOHQ</recordid><startdate>200911</startdate><enddate>200911</enddate><creator>Eng, P.C.</creator><creator>Khalil-Hani, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>200911</creationdate><title>FPGA-based embedded hand vein biometric authentication system</title><author>Eng, P.C. ; Khalil-Hani, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-740505aae1284925f51901f302d76695550e3f8fe74d1f1a6473926f4053dfab3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Authentication</topic><topic>Biometric</topic><topic>Biometrics</topic><topic>Embedded system</topic><topic>Feature extraction</topic><topic>Field programmable gate arrays</topic><topic>FPGA</topic><topic>Hand Vein</topic><topic>Nios2-linu</topic><topic>Operating systems</topic><topic>Prototypes</topic><topic>Real time systems</topic><topic>RTOS</topic><topic>Security</topic><topic>Veins</topic><toplevel>online_resources</toplevel><creatorcontrib>Eng, P.C.</creatorcontrib><creatorcontrib>Khalil-Hani, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Eng, P.C.</au><au>Khalil-Hani, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>FPGA-based embedded hand vein biometric authentication system</atitle><btitle>TENCON 2009 - 2009 IEEE Region 10 Conference</btitle><stitle>TENCON</stitle><date>2009-11</date><risdate>2009</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><issn>2159-3442</issn><eissn>2159-3450</eissn><isbn>9781424445462</isbn><isbn>1424445469</isbn><eisbn>1424445477</eisbn><eisbn>9781424445479</eisbn><abstract>Biometric authentication provides a high security and reliable approach to be used in security access system. However, this authentication method has not been widely implemented in a resource-constrained embedded system. In this project, we investigate a method of personal authentication based on infrared vein pattern in the back of the hand, targeted for embedded system which is implemented in Altera Nios II FPGA prototyping system, running on Real Time Operating System (RTOS). The RTOS applied is Nios2-Linux. A biometric feature is extracted from the vein pattern image and then matched for personal authentication. The algorithm consists of four modules: image capturing, image pre-processing, feature extraction, and the authentication module. These image processing algorithms executed in an embedded system with a 50 MHz fixed point processor. Preliminary experiment on a database of 82 images of 15 candidates show promising result with the system reaching equal error rate of 5.5%.</abstract><pub>IEEE</pub><doi>10.1109/TENCON.2009.5396173</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 2159-3442
ispartof TENCON 2009 - 2009 IEEE Region 10 Conference, 2009, p.1-5
issn 2159-3442
2159-3450
language eng
recordid cdi_ieee_primary_5396173
source IEEE Xplore All Conference Series
subjects Authentication
Biometric
Biometrics
Embedded system
Feature extraction
Field programmable gate arrays
FPGA
Hand Vein
Nios2-linu
Operating systems
Prototypes
Real time systems
RTOS
Security
Veins
title FPGA-based embedded hand vein biometric authentication system
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T15%3A58%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=FPGA-based%20embedded%20hand%20vein%20biometric%20authentication%20system&rft.btitle=TENCON%202009%20-%202009%20IEEE%20Region%2010%20Conference&rft.au=Eng,%20P.C.&rft.date=2009-11&rft.spage=1&rft.epage=5&rft.pages=1-5&rft.issn=2159-3442&rft.eissn=2159-3450&rft.isbn=9781424445462&rft.isbn_list=1424445469&rft_id=info:doi/10.1109/TENCON.2009.5396173&rft.eisbn=1424445477&rft.eisbn_list=9781424445479&rft_dat=%3Cieee_CHZPO%3E5396173%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-740505aae1284925f51901f302d76695550e3f8fe74d1f1a6473926f4053dfab3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5396173&rfr_iscdi=true