ML Anthology

Determining Wet Surfaces from Dry

Howard B. Mall Jr., Niels da Vitoria Lobo
ICCV 1995 pp. 963-968
doi:10.1109/ICCV.1995.466830 /iccv/1995/jr1995iccv-determining/

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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

ICCV Semantic Scholar

Cite

Text

Jr. and da Vitoria Lobo. "Determining Wet Surfaces from Dry." IEEE/CVF International Conference on Computer Vision, 1995. doi:10.1109/ICCV.1995.466830

Markdown

[Jr. and da Vitoria Lobo. "Determining Wet Surfaces from Dry." IEEE/CVF International Conference on Computer Vision, 1995.](https://mlanthology.org/iccv/1995/jr1995iccv-determining/) doi:10.1109/ICCV.1995.466830

BibTeX

@inproceedings{jr1995iccv-determining,
  title     = {{Determining Wet Surfaces from Dry}},
  author    = {Jr., Howard B. Mall and da Vitoria Lobo, Niels},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1995},
  pages     = {963-968},
  doi       = {10.1109/ICCV.1995.466830},
  url       = {https://mlanthology.org/iccv/1995/jr1995iccv-determining/}
}