Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/8796
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dc.contributor.authorSarsavadia, Riddhi-
dc.date.accessioned2019-08-29T10:14:56Z-
dc.date.available2019-08-29T10:14:56Z-
dc.date.issued2018-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/8796-
dc.description.abstractFeatures of Human face can be used to identify human uniquely. This make Face recognition system(FRS) popular for many applications like security verification at gate in many organizations, for access control of confidential resources, identifying intruders by national defence, and many more. With time, researchers and practitioners are putting efforts to rectify and optimize Intelligent Face Recognition System for different perspective, e.g. optimizing for accuracy, time, and space complexity, accuracy for facial expression change with time, face captured at some degree of orientation, lightning condition,occlusions etc.. As a result, many algorithms are available for face recognition system. This dissertation work focus to optimize IFRS for four criteria: i) face captured at more than 45 orientation, ii) person wearing eyeglass of different shape and size. iii) Face recognition using IP camera. Hence, we name it as "Intelligent face recognition system".en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries16MCEN17;-
dc.subjectComputer 2016en_US
dc.subjectProject Report 2016en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject16MCENen_US
dc.subject16MCEN17en_US
dc.subjectNTen_US
dc.subjectNT 2016en_US
dc.subjectCE (NT)en_US
dc.titleIntelligent Face Recognition Systemen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE (NT)

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