A fingerprint spoof detection based on MLP and SVM
We introduce a fingerprint spoof detection technique based on MLP and SVM that combines several features. The proposed technique is evaluated on two scenarios: (i) when an impostor can perform consecutive attempts to be considered authentic; and, (ii) when the system deals with fingerprints from eld...
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| creator | Pereira, L. F. A. Pinheiro, H. N. B. Silva, J. I. S. Silva, A. G. Pina, T. M. L. Cavalcanti, G. D. C. Tsang Ing Ren de Oliveira, J. P. N. |
| description | We introduce a fingerprint spoof detection technique based on MLP and SVM that combines several features. The proposed technique is evaluated on two scenarios: (i) when an impostor can perform consecutive attempts to be considered authentic; and, (ii) when the system deals with fingerprints from elderly people. In order to analyze these scenarios, a database was developed. The results show that the proposed combination of features increases the system performance in at least 33.56% and that the average error increases as more attempts for acceptance are allowed. The SVM classifier presents better performance in almost all the tested configurations. However, MLP is more accurate with biometrics from elderly people. |
| doi_str_mv | 10.1109/IJCNN.2012.6252582 |
| format | Conference Proceeding |
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F. A. ; Pinheiro, H. N. B. ; Silva, J. I. S. ; Silva, A. G. ; Pina, T. M. L. ; Cavalcanti, G. D. C. ; Tsang Ing Ren ; de Oliveira, J. P. N.</creator><creatorcontrib>Pereira, L. F. A. ; Pinheiro, H. N. B. ; Silva, J. I. S. ; Silva, A. G. ; Pina, T. M. L. ; Cavalcanti, G. D. C. ; Tsang Ing Ren ; de Oliveira, J. P. N.</creatorcontrib><description>We introduce a fingerprint spoof detection technique based on MLP and SVM that combines several features. The proposed technique is evaluated on two scenarios: (i) when an impostor can perform consecutive attempts to be considered authentic; and, (ii) when the system deals with fingerprints from elderly people. In order to analyze these scenarios, a database was developed. The results show that the proposed combination of features increases the system performance in at least 33.56% and that the average error increases as more attempts for acceptance are allowed. 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The results show that the proposed combination of features increases the system performance in at least 33.56% and that the average error increases as more attempts for acceptance are allowed. The SVM classifier presents better performance in almost all the tested configurations. 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N.</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>Pereira, L. F. A.</au><au>Pinheiro, H. N. B.</au><au>Silva, J. I. S.</au><au>Silva, A. G.</au><au>Pina, T. M. L.</au><au>Cavalcanti, G. D. C.</au><au>Tsang Ing Ren</au><au>de Oliveira, J. P. N.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A fingerprint spoof detection based on MLP and SVM</atitle><btitle>The 2012 International Joint Conference on Neural Networks (IJCNN)</btitle><stitle>IJCNN</stitle><date>2012-01-01</date><risdate>2012</risdate><spage>1</spage><epage>7</epage><pages>1-7</pages><issn>2161-4393</issn><eissn>2161-4407</eissn><isbn>9781467314886</isbn><isbn>1467314889</isbn><eisbn>9781467314893</eisbn><eisbn>9781467314909</eisbn><eisbn>1467314897</eisbn><eisbn>1467314900</eisbn><abstract>We introduce a fingerprint spoof detection technique based on MLP and SVM that combines several features. The proposed technique is evaluated on two scenarios: (i) when an impostor can perform consecutive attempts to be considered authentic; and, (ii) when the system deals with fingerprints from elderly people. In order to analyze these scenarios, a database was developed. The results show that the proposed combination of features increases the system performance in at least 33.56% and that the average error increases as more attempts for acceptance are allowed. The SVM classifier presents better performance in almost all the tested configurations. However, MLP is more accurate with biometrics from elderly people.</abstract><pub>IEEE</pub><doi>10.1109/IJCNN.2012.6252582</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 2161-4393 |
| ispartof | The 2012 International Joint Conference on Neural Networks (IJCNN), 2012, p.1-7 |
| issn | 2161-4393 2161-4407 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biometrics Feature extraction Senior citizens Support vector machines Training Vectors |
| title | A fingerprint spoof detection based on MLP and SVM |
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