Face recognition using 1DLBP, DWT and SVM

dc.contributor.authorBenzaoui, Amir
dc.date.accessioned2019-11-12T08:57:17Z
dc.date.available2019-11-12T08:57:17Z
dc.date.issued2015-05-25
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.identifier.citationIEEEen_US
dc.identifier.urihttp://172.16.99.83:4000/handle/123456789/6222
dc.language.isoenen_US
dc.publisheruniversity bouiraen_US
dc.titleFace recognition using 1DLBP, DWT and SVMen_US
dc.typeArticleen_US

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