Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1766
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dc.contributor.authorBakshi, S-
dc.contributor.authorKumari, S-
dc.contributor.authorRaman, R-
dc.contributor.authorSa, Pankaj K-
dc.date.accessioned2012-10-09T11:12:07Z-
dc.date.available2012-10-09T11:12:07Z-
dc.date.issued2012-04-
dc.identifier.citationInternational Conference on Modelling Optimization and Computing (ICMOC 2012)en
dc.identifier.urihttp://hdl.handle.net/2080/1766-
dc.descriptionCopyright belongs to Elsevieren
dc.description.abstractRecognition of a person through his face is the primitive mean of human identification. Identifying a person through face biometric have grown its importance through the last decade and researchers have attempted to find unique facial feature-points. Facial data also contains change with expression and age, which makes recognition through face difficult. And there has developed a stringent necessity to identify a person on partial facial data. These motives led researchers derive auxiliary biometric traits from facial image, viz. ear, lip and periocular region. In particular, periocular region has been exploited to examine the existence of uniqueness as there are many nodal points in periocular region. Classification and recognition is achieved through periocular region which shows significant accuracy, given the fact that periocular biometric uses only 25% of a complete face data.en
dc.format.extent186989 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherElsevieren
dc.subjectFaceen
dc.subjectPeriocular biometricen
dc.subjectRecognitionen
dc.subjectClassificationen
dc.titleEvaluation of Periocular over Face Biometric: A Case Studyen
dc.typeArticleen
Appears in Collections:Conference Papers

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