How to Measure Biometric Information?
Being able to measure the actual information content of biometrics is very important but also a challenging problem. Main difficulty here is not only related to the selected feature representation of the biometric data, but also related to the matching algorithm employed in biometric systems. In thi...
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| creator | Sutcu, Yagiz Sencar, Husrev T Memon, Nasir |
| description | Being able to measure the actual information content of biometrics is very important but also a challenging problem. Main difficulty here is not only related to the selected feature representation of the biometric data, but also related to the matching algorithm employed in biometric systems. In this paper, we propose a new measure for measuring biometric information using relative entropy between intra-user and inter-user distance distributions. As an example, we evaluated the proposed measure on a face image dataset. |
| doi_str_mv | 10.1109/ICPR.2010.363 |
| format | Conference Proceeding |
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As an example, we evaluated the proposed measure on a face image dataset.</description><subject>Artificial neural networks</subject><subject>Bioinformatics</subject><subject>biometric information</subject><subject>Entropy</subject><subject>Estimation</subject><subject>Face</subject><subject>Principal component analysis</subject><subject>relative entropy</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>1424475422</isbn><isbn>9781424475421</isbn><isbn>9781424475414</isbn><isbn>9780769541099</isbn><isbn>1424475414</isbn><isbn>0769541097</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jE1LxDAUAOMXWNcePXnpxWPX917ykvYkblG3sKLI3pckTSBgt9JWxH_vgnoahoER4gphiQj1bdu8vi0JDiq1PBJ5bSpUpJRhhepYZFRJLM1BT8TFfyA6FRkCY6k047nIpyk5IG20YeZM3KyHr2Ieiudgp88xFKs09GEeky_afRzG3s5p2N9dirNo36eQ_3Ehto8P22Zdbl6e2uZ-U6Ya5jIyk6qhQiZQtSYlVaeBO0vko1c-VtFF1xnVEVIEti54o71zvpIANsiFuP7dphDC7mNMvR2_d8y1QUPyB5rvQx4</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Sutcu, Yagiz</creator><creator>Sencar, Husrev T</creator><creator>Memon, Nasir</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201008</creationdate><title>How to Measure Biometric Information?</title><author>Sutcu, Yagiz ; Sencar, Husrev T ; Memon, Nasir</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-f552490815204962434d605da22cfc4cf8fbfbd74d212f05abec76cbbc8300ae3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Artificial neural networks</topic><topic>Bioinformatics</topic><topic>biometric information</topic><topic>Entropy</topic><topic>Estimation</topic><topic>Face</topic><topic>Principal component analysis</topic><topic>relative entropy</topic><toplevel>online_resources</toplevel><creatorcontrib>Sutcu, Yagiz</creatorcontrib><creatorcontrib>Sencar, Husrev T</creatorcontrib><creatorcontrib>Memon, Nasir</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sutcu, Yagiz</au><au>Sencar, Husrev T</au><au>Memon, Nasir</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>How to Measure Biometric Information?</atitle><btitle>2010 20th International Conference on Pattern Recognition</btitle><stitle>ICPR</stitle><date>2010-08</date><risdate>2010</risdate><spage>1469</spage><epage>1472</epage><pages>1469-1472</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>1424475422</isbn><isbn>9781424475421</isbn><eisbn>9781424475414</eisbn><eisbn>9780769541099</eisbn><eisbn>1424475414</eisbn><eisbn>0769541097</eisbn><abstract>Being able to measure the actual information content of biometrics is very important but also a challenging problem. Main difficulty here is not only related to the selected feature representation of the biometric data, but also related to the matching algorithm employed in biometric systems. In this paper, we propose a new measure for measuring biometric information using relative entropy between intra-user and inter-user distance distributions. As an example, we evaluated the proposed measure on a face image dataset.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.2010.363</doi><tpages>4</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Artificial neural networks Bioinformatics biometric information Entropy Estimation Face Principal component analysis relative entropy |
| title | How to Measure Biometric Information? |
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