NEW MULTIPLE CLASSIFIER SYSTEMS FOR FACE AUTHENTIFICATION

  • A. OUAMANE
  • M. BELAHCENE

Résumé

In this paper a multiple classifier systems for face verification is proposed based on the study of scores fusion for four face
authentication systems. Extraction features is realized by the Gabor wavelets phases, Principal Component Analysis (PCA)
with the Enhanced Fisher linear discriminant Model (EFM) are used as a method of reducing data space. For the study of
fusion of scores we used two approaches, the first based on the classification of scores using Fisher statistical method, Support
Vector Machine (SVM) and artificial neural networks (MLP) and the second is based on combinations of scores by the
weighted sum and fuzzy logic.

 

 

 

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Comment citer
OUAMANE, A.; BELAHCENE, M.. NEW MULTIPLE CLASSIFIER SYSTEMS FOR FACE AUTHENTIFICATION. Courrier du Savoir, [S.l.], v. 18, juin 2014. ISSN 1112-3338. Disponible à l'adresse : >http://revues.univ-biskra.dz/index.php/cds/article/view/649>. Date de consultation : 02 jui. 2020
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