• DocumentCode
    3318145
  • Title

    Determining wet surfaces from dry

  • Author

    Mall, Howard B., Jr. ; Da Vitoria Lobo, N.

  • Author_Institution
    Dept. of Comput. Sci., Central Florida Univ., Orlando, FL, USA
  • fYear
    1995
  • fDate
    20-23 Jun 1995
  • Firstpage
    963
  • Lastpage
    968
  • Abstract
    Wet surfaces are ubiquitous in our visual experience. Autonomous machines with vision systems will need to identify wet surfaces from dry. Wet surfaces (especially rough, absorbent ones) appear darker when wet. This paper presents the Lekner and Dorf (1988) model for describing the darkening caused by wetting. We explain how to use this optics model to transform intensity values of a region of an image to make that region appear wet. We also show how the model can be reversed in order to make a wet part of an image appear dry. It is also shown that this technique can be used to identify wet regions. This identification is contrasted with darkening caused by shadows. Comparisons of the gray-level histograms of these real images show the validity of this approach for distinguishing wet surfaces from dry
  • Keywords
    brightness; computer vision; image segmentation; image texture; wetting; darkening; dry surfaces; gray-level histograms; light intensity values; model reversal; optics model; rough absorbent surfaces; shadows; vision systems; visual experience; wet regions identification; wet surfaces; wetting; Computer science; Computer vision; Histograms; Machine vision; Navigation; Optical films; Optical scattering; Rough surfaces; Service robots; Surface roughness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1995. Proceedings., Fifth International Conference on
  • Conference_Location
    Cambridge, MA
  • Print_ISBN
    0-8186-7042-8
  • Type

    conf

  • DOI
    10.1109/ICCV.1995.466830
  • Filename
    466830