Please use this identifier to cite or link to this item: http://archives.univ-biskra.dz/handle/123456789/4253
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dc.contributor.authorM.Fedias-
dc.contributor.authorD.Saigaa-
dc.date.accessioned2014-11-25T07:24:15Z-
dc.date.available2014-11-25T07:24:15Z-
dc.date.issued2014-11-25-
dc.identifier.urihttp://archives.univ-biskra.dz/handle/123456789/4253-
dc.description.abstractIn this paper, we propose to introduce the color information to authenticate face. To improve the performance of this system, many color spaces have been used for processing RGB color components of the original images. The results in different spaces or components colorimetric are combined by using a nonlinear fusion for classification with networks neurons simple type MLP (Multi layer perceptron). We have applied the method of principal components analysis (PCA) or (Eignenfaces) for the extraction of feature vectors. To validate this work we have tested this approach on front images of the database XM2VTS according to its Associated Protocol (Protocol of Lausanne).en_US
dc.language.isoenen_US
dc.subjectEigenfaces, principal components analysis (ACP), face authentication, color spaces.en_US
dc.titleNonlinear Fusion of colors to face authenticationen_US
dc.typeArticleen_US
Appears in Collections:Communications Internationales

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