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Natural Material Recognition with Illumination Invariant Textural Features

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    SYSNO ASEP0346560
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleNatural Material Recognition with Illumination Invariant Textural Features
    Author(s) Vácha, Pavel (UTIA-B) RID
    Haindl, Michal (UTIA-B) RID, ORCID
    Source Title20th International Conference on Pattern Recognition. - Los Alamitos : IEEE Computer Society CPS, 2010 - ISSN 1051-4651 - ISBN 978-1-4244-7542-1
    Pagess. 858-861
    Number of pages4 s.
    Action20th International Conference on Pattern Recognition ICPR 2010
    Event date23.08.2010-26.08.2010
    VEvent locationIstanbul
    CountryTR - Turkey
    Event typeWRD
    Languageeng - English
    CountryUS - United States
    Keywordstexture ; colour ; Markov random field ; illumination invariance
    Subject RIVBD - Theory of Information
    R&D Projects1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    GA102/08/0593 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10750506 - UTIA-B (2005-2011)
    DOI10.1109/ICPR.2010.216
    AnnotationA visual appearance of natural materials fundamentally depends on illumination conditions, which significantly complicates a real scene analysis. We propose textural features based on fast Markovian statistics, which are simultaneously invariant to illumination colour and robust to illumination direction. No knowledge of illumination conditions is required and a recognition is possible from a single training image per material. Material recognition is tested on the currently most realistic visual representation - Bidirectional Texture Function (BTF), using the Amsterdam Library of Textures (ALOT), which contains 250 natural materials acquired in different illumination conditions. Our proposed features significantly outperform several leading alternatives including Local Binary Patterns (LBP, LBP-HF) and Gabor features.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2011
Number of the records: 1  

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