• DocumentCode
    2483250
  • Title

    Natural Material Recognition with Illumination Invariant Textural Features

  • Author

    Vácha, Pavel ; Haindl, Michal

  • Author_Institution
    Inst. of Inf. Theor. & Autom., ASCR, Prague, Czech Republic
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    858
  • Lastpage
    861
  • Abstract
    A 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.
  • Keywords
    Markov processes; image colour analysis; image texture; bidirectional texture function; fast Markovian statistics; illumination colour; illumination conditions; illumination direction; illumination invariant textural features; natural material recognition; scene analysis; visual representation; Computational modeling; Image color analysis; Lighting; Materials; Pattern recognition; Pixel; Training; Markov random field; colour; illumination invariance; texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.216
  • Filename
    5596064