Genetic algorithm based feature selection level fusion using fingerprint and iris biometrics

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dc.contributor.authorAltun, Adem Alpaslan
dc.contributor.authorKoçer, H. Erdinç
dc.contributor.authorAllahverdi, Novruz
dc.date.accessioned2020-03-26T17:26:57Z
dc.date.available2020-03-26T17:26:57Z
dc.date.issued2008
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractAn accuracy level of unimodal biometric recognition system is not very high because of noisy data, limited degrees of freedom, spoof attacks etc. problems. A multimodal biometric system which uses two or more biometric traits of an individual can overcome such problems. We propose a multimodal biometric recognition system that fuses the fingerprint and iris features at the feature extraction level. A feed-forward artificial neural networks (ANNs) model is used for recognition of a person. There is a need to make the training time shorter, so the feature selection level should be performed. A genetic algorithms (GAs) approach is used for feature selection of a combined data. As an experiment, the database of 60 users, 10 fingerprint images and 10 iris images taken from each person, is used. The test results are presented in the last stage of this research.en_US
dc.identifier.doi10.1142/S0218001408006351en_US
dc.identifier.endpage600en_US
dc.identifier.issn0218-0014en_US
dc.identifier.issn1793-6381en_US
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage585en_US
dc.identifier.urihttps://dx.doi.org/10.1142/S0218001408006351
dc.identifier.urihttps://hdl.handle.net/20.500.12395/22425
dc.identifier.volume22en_US
dc.identifier.wosWOS:000255842700012en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTDen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCEen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectmultibiometricen_US
dc.subjectfeature selectionen_US
dc.subjectgenetic algorithmsen_US
dc.subjectartificial neural networksen_US
dc.titleGenetic algorithm based feature selection level fusion using fingerprint and iris biometricsen_US
dc.typeArticleen_US

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