• DocumentCode
    79723
  • Title

    Image-Based Separation of Reflective and Fluorescent Components Using Illumination Variant and Invariant Color

  • Author

    Zhang, Chenghui ; Sato, Imari

  • Volume
    35
  • Issue
    12
  • fYear
    2013
  • fDate
    Dec. 2013
  • Firstpage
    2866
  • Lastpage
    2877
  • Abstract
    Traditionally, researchers tend to exclude fluorescence from color appearance algorithms in computer vision and image processing because of its complexity. In reality, fluorescence is a very common phenomenon observed in many objects, from gems and corals, to different kinds of writing paper, and to our clothes. In this paper, we provide detailed theories of fluorescence phenomenon. In particular, we show that the color appearance of fluorescence is unaffected by illumination in which it differs from ordinary reflectance. Moreover, we show that the color appearance of objects with reflective and fluorescent components can be represented as a linear combination of the two components. A linear model allows us to separate the two components using images taken under unknown illuminants using independent component analysis (ICA). The effectiveness of the proposed method is demonstrated using digital images of various fluorescent objects.
  • Keywords
    computer vision; fluorescence; image colour analysis; image representation; independent component analysis; lighting; reflectivity; ICA; clothes; color appearance algorithm; color appearance representation; complexity; computer vision; corals; fluorescence phenomenon; gems; illumination variant; image processing; image-based fluorescent component separation; image-based reflective component separation; independent component analysis; invariant color; linear model; ordinary reflectance; writing paper; Emissions; Fluorescence; Image color analysis; Light sources; Lighting; Surface waves; Wavelength measurement; Reflectance components separation; diffuse reflection; fluorescence emission; illumination;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2012.255
  • Filename
    6365191