Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/2114
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dc.contributor.authorDagher, Issamen_US
dc.contributor.authorBazzaz, Hussein Alen_US
dc.date.accessioned2020-12-23T09:06:36Z-
dc.date.available2020-12-23T09:06:36Z-
dc.date.issued2019-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/2114-
dc.description.abstractThis paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face component detection and cropping. The facial components are detected and cropped accurately during all pose-changing circumstances. The cropped components are represented by the histogram of oriented gradients (HOG). The weight of each component was determined using a validation process. Combining these weights was done by a simple voting technique. Three public databases were used: the AT&T database, the PUT database, and the AR database. Several improvements are observed using the weighted voting recognition method presented in this paper.en_US
dc.language.isoengen_US
dc.titleImproving the component-based face recognition using enhanced Viola-Jones and weighted voting techniqueen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1155/2019/8234124-
dc.contributor.affiliationDepartment of Computer Engineeringen_US
dc.description.volume2019en_US
dc.date.catalogued2020-02-20-
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=https://doi.org/10.1155/2019/8234124en_US
dc.identifier.OlibID252575-
dc.relation.ispartoftextJournal of modelling and simulation in engineeringen_US
dc.provenance.recordsourceOliben_US
crisitem.author.parentorgFaculty of Engineering-
Appears in Collections:Department of Computer Engineering
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