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
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;
Conference_Titel :
Computer Vision, 1995. Proceedings., Fifth International Conference on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-8186-7042-8
DOI :
10.1109/ICCV.1995.466830