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    Kernel discriminant analysis for color face recognition

    Access Status
    Fulltext not available
    Authors
    Zhang, X.
    Liu, Wan-Quan
    An, S.
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Zhang, X. and Liu, W. and An, S. 2012. Kernel discriminant analysis for color face recognition. ICIC Express Letters. 6 (3): pp. 759-764.
    Source Title
    ICIC Express Letters
    ISSN
    1881-803X
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/30551
    Collection
    • Curtin Research Publications
    Abstract

    A lot of algorithms for face recognition have been proposed in current literature and they are mainly for gray images. They will have some limitations when applying to color face images. In this paper, a novel kernel method is developed with an aim to improve the performance for color face recognition. Technically, this method will combine kernel method with Linear Discriminant Analysis for color face models. Intuitively the color space can provide extra discriminant information and the kernel method will provide the nonlinear discriminant capability. Their combination will take both advantages and can improve the recognition performance significantly as demonstrated in the extensive experiments. Experiments are done on GT, AR and FERET databases, and the proposed method outperforms other related methods with variations on facial expressions, poses and lighting conditions, and it is especially superior in aging effect with the performance doubled. © 2012 ICIC International.

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