Facial recognition using new LBP representations

Alireza Akoushideh, Raymond N.J. Veldhuis, Lieuwe Jan Spreeuwers, Babak M.-N. Maybodi

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    In this paper, we propose a facial recognition based on the LBP operator. We divide the face into non-overlapped regions. After that, we classify a training set using each region at a time under different configurations of the LBP operator. Regarding to the best recognition rate, we consider a weight and specific LBP configuration to the regions. To represent the face image, we extract LBP histograms with the specific configuration (radius and neighbors) and concatenate them into feature histogram. We propose a multi-resolution approach, to gather local and global information and improve the recognition rate. To evaluate our proposed approach, we considered the FERET data set, which includes different facial expressions, lighting, and aging of the subjects. In addition, weighted Chi-2 is considered as a dissimilarity measure. The experimental results show a considerable improvement against the original idea.
    Original languageUndefined
    Title of host publicationProceedings of the 36th WIC Symposium on Information Theory in the Benelux
    Place of PublicationBrussels
    PublisherUniversité Libre de Bruxelles
    Number of pages8
    ISBN (Print)978-2-8052-0277-3
    Publication statusPublished - 6 May 2015
    Event36th WIC Symposium on Information Theory in the Benelux 2015 - Brussels, Belgium
    Duration: 6 May 20157 May 2015
    Conference number: 36

    Publication series

    PublisherUniversité libre de Bruxelles


    Workshop36th WIC Symposium on Information Theory in the Benelux 2015


    • EWI-26076
    • SCS-Safety
    • Biometrics
    • IR-96057
    • Local Binary Patterns
    • METIS-312634
    • Face Recognition

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