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Finger knuckle biometrics – A review
[Display omitted] •Describes the role of finger knuckle surface in biometric authentication.•Enumerates various available open datasets for finger knuckle biometric trait.•Presents different view point in the classification of various finger knuckle feature recognition methods.•Elaborates on finger...
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Published in: | Computers & electrical engineering 2015-07, Vol.45, p.249-259 |
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container_title | Computers & electrical engineering |
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creator | Usha, K. Ezhilarasan, M. |
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•Describes the role of finger knuckle surface in biometric authentication.•Enumerates various available open datasets for finger knuckle biometric trait.•Presents different view point in the classification of various finger knuckle feature recognition methods.•Elaborates on finger knuckle surface preprocessing, feature extraction, classification and fusion methodologies.•Addresses significant issues that are mandatory for deploying finger knuckle biometric system.
Biometric-based personal authentication is receiving a widespread interest in the area of research due to its high applicability in a wide range of security applications. Among these, hand-based biometric systems are considered to be more successful in terms of accuracy and computational complexity. In hand-based biometrics, finger knuckle surface is considered as one of the emerging potential biometric traits for personal authentication. This is due to its stable and unique inherent patterns present in the outer surface of the finger back knuckle region. Further, this finger knuckle has a high potentiality towards discriminating individuals with high accuracy. In this paper, we present a review of various system models that are implemented for personal authentication using finger knuckle biometrics. Furthermore, the challenges that could arise during the implementation of the large scale real time biometric system with finger knuckle print are explored. |
doi_str_mv | 10.1016/j.compeleceng.2014.11.008 |
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•Describes the role of finger knuckle surface in biometric authentication.•Enumerates various available open datasets for finger knuckle biometric trait.•Presents different view point in the classification of various finger knuckle feature recognition methods.•Elaborates on finger knuckle surface preprocessing, feature extraction, classification and fusion methodologies.•Addresses significant issues that are mandatory for deploying finger knuckle biometric system.
Biometric-based personal authentication is receiving a widespread interest in the area of research due to its high applicability in a wide range of security applications. Among these, hand-based biometric systems are considered to be more successful in terms of accuracy and computational complexity. In hand-based biometrics, finger knuckle surface is considered as one of the emerging potential biometric traits for personal authentication. This is due to its stable and unique inherent patterns present in the outer surface of the finger back knuckle region. Further, this finger knuckle has a high potentiality towards discriminating individuals with high accuracy. In this paper, we present a review of various system models that are implemented for personal authentication using finger knuckle biometrics. Furthermore, the challenges that could arise during the implementation of the large scale real time biometric system with finger knuckle print are explored.</description><identifier>ISSN: 0045-7906</identifier><identifier>EISSN: 1879-0755</identifier><identifier>DOI: 10.1016/j.compeleceng.2014.11.008</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Accuracy ; Authentication ; Biometrics ; Computer information security ; Computer simulation ; Electrical engineering ; Equal error rate ; Finger knuckle surface ; Fingers ; Genuine acceptance rate ; Geometric analysis ; Receiving ; Texture analysis</subject><ispartof>Computers & electrical engineering, 2015-07, Vol.45, p.249-259</ispartof><rights>2014 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c354t-36cdf26163cbfdcefe0b0d0d32c14d1c8f6d02ff91ad9bd2db38cc429a122b13</citedby><cites>FETCH-LOGICAL-c354t-36cdf26163cbfdcefe0b0d0d32c14d1c8f6d02ff91ad9bd2db38cc429a122b13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Usha, K.</creatorcontrib><creatorcontrib>Ezhilarasan, M.</creatorcontrib><title>Finger knuckle biometrics – A review</title><title>Computers & electrical engineering</title><description>[Display omitted]
•Describes the role of finger knuckle surface in biometric authentication.•Enumerates various available open datasets for finger knuckle biometric trait.•Presents different view point in the classification of various finger knuckle feature recognition methods.•Elaborates on finger knuckle surface preprocessing, feature extraction, classification and fusion methodologies.•Addresses significant issues that are mandatory for deploying finger knuckle biometric system.
Biometric-based personal authentication is receiving a widespread interest in the area of research due to its high applicability in a wide range of security applications. Among these, hand-based biometric systems are considered to be more successful in terms of accuracy and computational complexity. In hand-based biometrics, finger knuckle surface is considered as one of the emerging potential biometric traits for personal authentication. This is due to its stable and unique inherent patterns present in the outer surface of the finger back knuckle region. Further, this finger knuckle has a high potentiality towards discriminating individuals with high accuracy. In this paper, we present a review of various system models that are implemented for personal authentication using finger knuckle biometrics. Furthermore, the challenges that could arise during the implementation of the large scale real time biometric system with finger knuckle print are explored.</description><subject>Accuracy</subject><subject>Authentication</subject><subject>Biometrics</subject><subject>Computer information security</subject><subject>Computer simulation</subject><subject>Electrical engineering</subject><subject>Equal error rate</subject><subject>Finger knuckle surface</subject><subject>Fingers</subject><subject>Genuine acceptance rate</subject><subject>Geometric analysis</subject><subject>Receiving</subject><subject>Texture analysis</subject><issn>0045-7906</issn><issn>1879-0755</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkM1Kw0AUhQdRsFbfIW7ETeK9k2SaLEvxDwpuuh-SO3fKtPmpM6niznfwDX0SU-rCpavDgXMOnE-Ia4QEAdXdJqG-3XHDxN06kYBZgpgAFCdigsWsjGGW56diApDl8awEdS4uQtjA6BUWE3Hz4Lo1-2jb7WnbcFS7vuXBOwrR9-dXNI88vzl-vxRntmoCX_3qVKwe7leLp3j58vi8mC9jSvNsiFNFxkqFKqXaGmLLUIMBk0rCzCAVVhmQ1pZYmbI20tRpQZTJskIpa0yn4vY4u_P9657DoFsXiJum6rjfB40FKkghzw7R8hgl34fg2eqdd23lPzSCPqDRG_0HjT6g0Yh6RDN2F8cuj1fGe14HctwRG-eZBm1694-VHxQvc3A</recordid><startdate>201507</startdate><enddate>201507</enddate><creator>Usha, K.</creator><creator>Ezhilarasan, M.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201507</creationdate><title>Finger knuckle biometrics – A review</title><author>Usha, K. ; Ezhilarasan, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c354t-36cdf26163cbfdcefe0b0d0d32c14d1c8f6d02ff91ad9bd2db38cc429a122b13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Accuracy</topic><topic>Authentication</topic><topic>Biometrics</topic><topic>Computer information security</topic><topic>Computer simulation</topic><topic>Electrical engineering</topic><topic>Equal error rate</topic><topic>Finger knuckle surface</topic><topic>Fingers</topic><topic>Genuine acceptance rate</topic><topic>Geometric analysis</topic><topic>Receiving</topic><topic>Texture analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Usha, K.</creatorcontrib><creatorcontrib>Ezhilarasan, M.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & electrical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Usha, K.</au><au>Ezhilarasan, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Finger knuckle biometrics – A review</atitle><jtitle>Computers & electrical engineering</jtitle><date>2015-07</date><risdate>2015</risdate><volume>45</volume><spage>249</spage><epage>259</epage><pages>249-259</pages><issn>0045-7906</issn><eissn>1879-0755</eissn><abstract>[Display omitted]
•Describes the role of finger knuckle surface in biometric authentication.•Enumerates various available open datasets for finger knuckle biometric trait.•Presents different view point in the classification of various finger knuckle feature recognition methods.•Elaborates on finger knuckle surface preprocessing, feature extraction, classification and fusion methodologies.•Addresses significant issues that are mandatory for deploying finger knuckle biometric system.
Biometric-based personal authentication is receiving a widespread interest in the area of research due to its high applicability in a wide range of security applications. Among these, hand-based biometric systems are considered to be more successful in terms of accuracy and computational complexity. In hand-based biometrics, finger knuckle surface is considered as one of the emerging potential biometric traits for personal authentication. This is due to its stable and unique inherent patterns present in the outer surface of the finger back knuckle region. Further, this finger knuckle has a high potentiality towards discriminating individuals with high accuracy. In this paper, we present a review of various system models that are implemented for personal authentication using finger knuckle biometrics. Furthermore, the challenges that could arise during the implementation of the large scale real time biometric system with finger knuckle print are explored.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.compeleceng.2014.11.008</doi><tpages>11</tpages></addata></record> |
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subjects | Accuracy Authentication Biometrics Computer information security Computer simulation Electrical engineering Equal error rate Finger knuckle surface Fingers Genuine acceptance rate Geometric analysis Receiving Texture analysis |
title | Finger knuckle biometrics – A review |
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