Please use this identifier to cite or link to this item: http://dspace.univ-bouira.dz:8080/jspui/handle/123456789/6222
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBenzaoui, Amir-
dc.date.accessioned2019-11-12T08:57:17Z-
dc.date.available2019-11-12T08:57:17Z-
dc.date.issued2015-05-25-
dc.identifier.citationIEEEen_US
dc.identifier.urihttp://dspace.univ-bouira.dz:8080/jspui/handle/123456789/6222-
dc.description.abstractThe popular Local binary patterns (LBP) have been highly successful in describing and recognizing faces. However, the original LBP has several limitations which must to be optimized in order to improve its performances to make it suitable for the needs of different types of problems. In this paper, we investigate a new local texture descriptor for automated human identification using 2D facial imaging, this descriptor, denoted: One Dimensional Local Binary Pattern (1DLBP), produces binary code and inspired from classical LBP. The performances of the textural descriptor have been improved by the introduction of the wavelets in order to reduce the dimensionalities of the resulting vectors without losing information. The 1DLBP descriptor is assessed in comparison to the classical and the extended versions of the LBP descriptor. The experimental results applied on two publically datasets, which are the ORL and AR …en_US
dc.language.isoenen_US
dc.publisheruniversity bouiraen_US
dc.titleFace recognition using 1DLBP, DWT and SVMen_US
dc.typeArticleen_US
Appears in Collections:Articles

Files in This Item:
File Description SizeFormat 
07233002.pdf610,46 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.