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    Face recognition based two dimensional locality preserving projection in frequency domain

    Access Status
    Fulltext not available
    Authors
    Lu, C.
    Liu, X.
    Liu, Wan-Quan
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Lu, C. and Liu, X. and Liu, W. 2012. Face recognition based two dimensional locality preserving projection in frequency domain. Neurocomputing. 98: pp. 135-142.
    Source Title
    Neurocomputing
    DOI
    10.1016/j.neucom.2011.08.045
    ISSN
    0925-2312
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/9608
    Collection
    • Curtin Research Publications
    Abstract

    In this paper we propose a new face recognition method based on two-dimensional locality preserving projections (2DLPP) in frequency domain. For this purpose, we first introduce the two-dimensional locality preserving projections. Then the 2DLPP in frequency domain is proposed for face recognition. In fact, two dimensional discrete cosine transform (2DDCT) is used as a pre-processing step and it transforms the face image signals from spatial domain into frequency domain aiming to reduce the effects of illumination and pose changes in face recognition. Then 2DLPP is applied on the upper left corner blocks of the 2DDCT transformed matrices, which represent main energy of each original image. For demonstration, the Olivetti Research Laboratory (ORL), YALE, FERET and YALE-B face datasets are used to compare the proposed approach with the conventional 2DLPP and 2DDCT approaches with the nearest neighborhood (NN) classifier. The experimental results show that the proposed 2DLPP in frequency domain is superior over the 2DLPP in spatial domain and 2DDCT itself in frequency domain.

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