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Improved Eigenface Recognition Using Hierarchal Technique

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dc.contributor.author El-Sayed, Ahmed en_US
dc.contributor.author Mahmood, Ausif en_US
dc.contributor.author Abualkibash, Munther Hamad en_US
dc.date.accessioned 2014-07-16T16:45:40Z
dc.date.available 2014-07-16T16:45:40Z
dc.date.issued 2012 en_US
dc.identifier.citation Poster 79 en_US
dc.identifier.other 8290ff68-0628-e76b-937e-a2207875fd12 en_US
dc.identifier.uri https://scholarworks.bridgeport.edu/xmlui/handle/123456789/597
dc.description Face recognition is one of the important fields of computer vision and pattern recognition because of its applications in security and intelligence systems. In this paper we improve one of the famous algorithms used for face recognition which is Eigenface technique. The method of improvement used in this paper is the Hierarchical technique which means that input image will be applied into different levels of recognition instead of only one level as used in the regular Eigenface method. The hierarchical technique developed in this paper increases the detection rate in the case of large benchmark image database by more than 30% as compared to the original method. en_US
dc.subject Faculty research day en_US
dc.title Improved Eigenface Recognition Using Hierarchal Technique en_US
dc.type Presentation en_US
dc.institute.department School of Engineering en_US
dc.institute.name University of Bridgeport en_US
dc.event.name Faculty Research Day en_US


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