Multi-Resolution Face Recognition: The Behaviors of Local Binary Pattern at Different Frequency Bands

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    Abstract

    This paper presents an analysis of the recognition performance of LBP at different frequency bands to exploit their discriminative information. The work presented in this paper is part of an investigation about which aspects of a face contribute to automated face recognition. Multi-resolution analysis, by means of wavelet transform, is commonly used to explore the features of an image. The each step of wavelet transform decomposes an image recursively into four frequency bands: approximation, horizontal, vertical, and diagonal band. The approximation band is a down sampled version of the original image. Whereas, the other bands are detail bands that contain detail information of the image in horizontal, vertical, and diagonal directions. The noise is more dominant in these bands. The information contained in the detail bands is more related to high frequency-components and local structures such as edges. In order to analyze the impact of the various bands, we performed classification experiments on them. For the A-bands, that contain the global information of the facial image, we used PCA/LDA classifiers. For the detail bands, that contain local structures, we used LBP.
    Original languageEnglish
    Title of host publicationProceedings of the 2019 Symposium on Information Theory and Signal Processing in the Benelux
    Subtitle of host publicationMay 28-29 2019, KU Leuven, Technologiecampus Gent, Belgium
    EditorsGilles Callebaut, Kevin Verniers, Bert Cox
    Place of PublicationLeuven
    PublisherWerkgemeenschap voor Informatie- en Communicatietheorie (WIC)
    Pages63-70
    Number of pages8
    ISBN (Print)978-94-918-5703-4
    Publication statusPublished - 28 May 2019
    Event40th WIC Symposium on Information Theory in the Benelux 2019 - Ghent Technology Campus, Leuven, Belgium
    Duration: 28 May 201929 May 2019
    Conference number: 40

    Conference

    Conference40th WIC Symposium on Information Theory in the Benelux 2019
    CountryBelgium
    CityLeuven
    Period28/05/1929/05/19

    Keywords

    • Multi-resolution analysis
    • Face recognition
    • Wavelet transform
    • Local binary patterns

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