Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/3166
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dc.contributor.advisorDaba, Jihad S.en_US
dc.contributor.authorKamel, Antoineen_US
dc.date.accessioned2020-12-23T14:33:59Z-
dc.date.available2020-12-23T14:33:59Z-
dc.date.issued2020-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/3166-
dc.descriptionIncludes bibliographical references (p. 31).en_US
dc.descriptionSupervised by Dr. Jihad Daba.en_US
dc.description.abstractBiometric systems have become way popular these days; A biometric trait such as a fingerprint is a lot more unique, portable and secured than a password or a physical card, you just cant forget or lose your fingerprint, nor it can be easily stolen or forged. Now moreover, a biometric system relying on multiple biometric traits (Multimodal) guarantees more security and is much more accurate and efficient than single-trait systems (Unimodal); It will take advantage of this combination of traits to overcome the limitations that single-trait systems pose. For instance, fingerprints might deteriorate over time with age, so the presence of Face Recognition alongside Fingerprint Recognition in one system can give the user the option to use one of the two or even both at the same time. We introduce in this paper a multimodal biometric system that combines both facial and palm recognition (traits) in order to authenticate the identity of the input user; We detail each part forming the system, starting from obtaining inputs, to region of interest (ROI) extraction, processing of each ROI, comparing results to the databases, generating scores then fusing them into one score in order to decide whether to authenticate or no.en_US
dc.description.statementofresponsibilityby Antoine Kamelen_US
dc.format.extent1 online resource (ix, 31 pages) :ill., tablesen_US
dc.language.isoengen_US
dc.rightsThis object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holderen_US
dc.subject.lcshBiometrics (Biology)en_US
dc.subject.lcshOptical data processingen_US
dc.subject.lcshPattern recognitionen_US
dc.titleApplication of a facial and palmprint based multimodal biometric systemen_US
dc.typeProjecten_US
dc.contributor.departmentDepartment of Computer Engineeringen_US
dc.contributor.facultyFaculty of Engineeringen_US
dc.contributor.institutionUniversity of Balamanden_US
dc.date.catalogued2020-06-16-
dc.description.degreeMS in Computer Engineeringen_US
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://olib.balamand.edu.lb/projects_and_theses/253365.pdfen_US
dc.identifier.OlibID253365-
dc.provenance.recordsourceOliben_US
Appears in Collections:UOB Theses and Projects
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