Abstract

We propose a system to detect wet surfaces using near infrared LED lighting and a conventional CCD camera. There is a sharp fall in the transmission of light through water for wavelengths longer than 920nm. By detecting this transition it is possible to robustly detect a film of water lying on a surface. This paper considers surfaces that are impermeable, are not hydrophilic, and are sufficiently reflective (reflectivity, ρ>0.4). A system is demonstrated that can detect water on a wide range of surfaces that meet these conditions.

© 2010 Optical Society of America

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References

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  1. R. Coss, S. Ruff, and T. Simms, “All that glistens II. The effects of reflective surface finishes on the mouthing activity of infants and toddlers,” Ecological Psychol. 15, 357–358 (2003).
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    [CrossRef]
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    [CrossRef]
  6. H. B. Mall, Jr. and N. da Vitoria Lobo, “Determining wet surfaces from dry,” in Proceedings of the Fifth International Conference on Computer Vision, 963–968 (IEEE Computer Society, 1995).
  7. I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
    [CrossRef] [PubMed]
  8. R. O. Dror, E. H. Adelson, and A. S. Willsky, “Recognition of surface reflectance properties from a single image under unknown real-world illumination,” in Proceedings of the IEEE Workshop on Identifying Objects across Variations in Lighting (IEEE, 2001).
  9. K. M. Hay, M. I. Dragila, and J. Liburdy, “Theoretical model for the wetting of a rough surface,” J. Colloid Interface Sci. 325, 472–477 (2008).
    [CrossRef] [PubMed]
  10. J. Workman and L. Weyer, Practical Guide to Interpretive Near-Infrared Spectroscopy (CRC Press, 2008).

2008

K. M. Hay, M. I. Dragila, and J. Liburdy, “Theoretical model for the wetting of a rough surface,” J. Colloid Interface Sci. 325, 472–477 (2008).
[CrossRef] [PubMed]

J. Workman and L. Weyer, Practical Guide to Interpretive Near-Infrared Spectroscopy (CRC Press, 2008).

2007

I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
[CrossRef] [PubMed]

2003

R. Coss, S. Ruff, and T. Simms, “All that glistens II. The effects of reflective surface finishes on the mouthing activity of infants and toddlers,” Ecological Psychol. 15, 357–358 (2003).
[CrossRef]

2001

R. O. Dror, E. H. Adelson, and A. S. Willsky, “Recognition of surface reflectance properties from a single image under unknown real-world illumination,” in Proceedings of the IEEE Workshop on Identifying Objects across Variations in Lighting (IEEE, 2001).

1999

H. W. Jensen, J. Legakis, and J. Dorsey, “Rendering of wet materials,” in Rendering Techniques (Springer, 1999), pp. 273–282.
[CrossRef]

1995

H. B. Mall, Jr. and N. da Vitoria Lobo, “Determining wet surfaces from dry,” in Proceedings of the Fifth International Conference on Computer Vision, 963–968 (IEEE Computer Society, 1995).

1988

1986

1925

A. Angstrom, “The albedo of various surfaces of ground,” Geografiska Ann. 7, 323 (1925).
[CrossRef]

Adelson, E. H.

I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
[CrossRef] [PubMed]

R. O. Dror, E. H. Adelson, and A. S. Willsky, “Recognition of surface reflectance properties from a single image under unknown real-world illumination,” in Proceedings of the IEEE Workshop on Identifying Objects across Variations in Lighting (IEEE, 2001).

Angstrom, A.

A. Angstrom, “The albedo of various surfaces of ground,” Geografiska Ann. 7, 323 (1925).
[CrossRef]

Bohren, C. F.

Coss, R.

R. Coss, S. Ruff, and T. Simms, “All that glistens II. The effects of reflective surface finishes on the mouthing activity of infants and toddlers,” Ecological Psychol. 15, 357–358 (2003).
[CrossRef]

da Vitoria Lobo, N.

H. B. Mall, Jr. and N. da Vitoria Lobo, “Determining wet surfaces from dry,” in Proceedings of the Fifth International Conference on Computer Vision, 963–968 (IEEE Computer Society, 1995).

Dorf, M. C.

Dorsey, J.

H. W. Jensen, J. Legakis, and J. Dorsey, “Rendering of wet materials,” in Rendering Techniques (Springer, 1999), pp. 273–282.
[CrossRef]

Dragila, M. I.

K. M. Hay, M. I. Dragila, and J. Liburdy, “Theoretical model for the wetting of a rough surface,” J. Colloid Interface Sci. 325, 472–477 (2008).
[CrossRef] [PubMed]

Dror, R. O.

R. O. Dror, E. H. Adelson, and A. S. Willsky, “Recognition of surface reflectance properties from a single image under unknown real-world illumination,” in Proceedings of the IEEE Workshop on Identifying Objects across Variations in Lighting (IEEE, 2001).

Hay, K. M.

K. M. Hay, M. I. Dragila, and J. Liburdy, “Theoretical model for the wetting of a rough surface,” J. Colloid Interface Sci. 325, 472–477 (2008).
[CrossRef] [PubMed]

Jensen, H. W.

H. W. Jensen, J. Legakis, and J. Dorsey, “Rendering of wet materials,” in Rendering Techniques (Springer, 1999), pp. 273–282.
[CrossRef]

Legakis, J.

H. W. Jensen, J. Legakis, and J. Dorsey, “Rendering of wet materials,” in Rendering Techniques (Springer, 1999), pp. 273–282.
[CrossRef]

Lekner, J.

Liburdy, J.

K. M. Hay, M. I. Dragila, and J. Liburdy, “Theoretical model for the wetting of a rough surface,” J. Colloid Interface Sci. 325, 472–477 (2008).
[CrossRef] [PubMed]

Mall, H. B.

H. B. Mall, Jr. and N. da Vitoria Lobo, “Determining wet surfaces from dry,” in Proceedings of the Fifth International Conference on Computer Vision, 963–968 (IEEE Computer Society, 1995).

Mergenthaler, J. L.

Motoyoshi, I.

I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
[CrossRef] [PubMed]

Nishida, Shin’ya

I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
[CrossRef] [PubMed]

Ruff, S.

R. Coss, S. Ruff, and T. Simms, “All that glistens II. The effects of reflective surface finishes on the mouthing activity of infants and toddlers,” Ecological Psychol. 15, 357–358 (2003).
[CrossRef]

Sharan, L.

I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
[CrossRef] [PubMed]

Simms, T.

R. Coss, S. Ruff, and T. Simms, “All that glistens II. The effects of reflective surface finishes on the mouthing activity of infants and toddlers,” Ecological Psychol. 15, 357–358 (2003).
[CrossRef]

Twomey, S. A.

Weyer, L.

J. Workman and L. Weyer, Practical Guide to Interpretive Near-Infrared Spectroscopy (CRC Press, 2008).

Willsky, A. S.

R. O. Dror, E. H. Adelson, and A. S. Willsky, “Recognition of surface reflectance properties from a single image under unknown real-world illumination,” in Proceedings of the IEEE Workshop on Identifying Objects across Variations in Lighting (IEEE, 2001).

Workman, J.

J. Workman and L. Weyer, Practical Guide to Interpretive Near-Infrared Spectroscopy (CRC Press, 2008).

Appl. Opt.

Ecological Psychol.

R. Coss, S. Ruff, and T. Simms, “All that glistens II. The effects of reflective surface finishes on the mouthing activity of infants and toddlers,” Ecological Psychol. 15, 357–358 (2003).
[CrossRef]

Geografiska Ann.

A. Angstrom, “The albedo of various surfaces of ground,” Geografiska Ann. 7, 323 (1925).
[CrossRef]

J. Colloid Interface Sci.

K. M. Hay, M. I. Dragila, and J. Liburdy, “Theoretical model for the wetting of a rough surface,” J. Colloid Interface Sci. 325, 472–477 (2008).
[CrossRef] [PubMed]

Nature

I. Motoyoshi, Shin’ya Nishida, L. Sharan, and E. H. Adelson, “Image statistics and the perception of surface qualities,” Nature 447, 206–209 (2007).
[CrossRef] [PubMed]

Other

R. O. Dror, E. H. Adelson, and A. S. Willsky, “Recognition of surface reflectance properties from a single image under unknown real-world illumination,” in Proceedings of the IEEE Workshop on Identifying Objects across Variations in Lighting (IEEE, 2001).

J. Workman and L. Weyer, Practical Guide to Interpretive Near-Infrared Spectroscopy (CRC Press, 2008).

H. W. Jensen, J. Legakis, and J. Dorsey, “Rendering of wet materials,” in Rendering Techniques (Springer, 1999), pp. 273–282.
[CrossRef]

H. B. Mall, Jr. and N. da Vitoria Lobo, “Determining wet surfaces from dry,” in Proceedings of the Fifth International Conference on Computer Vision, 963–968 (IEEE Computer Society, 1995).

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Figures (15)

Fig. 1
Fig. 1

Transmission spectra of light through various depths of water.

Fig. 2
Fig. 2

Reflectance spectra of various surface materials.

Fig. 3
Fig. 3

Reflectance spectra of several colorless liquids. Note that there is no spectral feature at 970 nm in these materials.

Fig. 4
Fig. 4

Arrangement of LEDs and filter on the lighting head. Four Band A LEDs are placed behind an interference filter; four Band B and Band C LEDs are placed around the filter.

Fig. 5
Fig. 5

Spectral output of light head.

Fig. 6
Fig. 6

Imaging geometry.

Fig. 7
Fig. 7

A plastic wedge was partially submerged to observe the effect of varying the depth of water on the spectral bands.

Fig. 8
Fig. 8

Ratios of band A pixel intensities to band B and band C pixel intensities, obtained by imaging a surface submerged to varying depths.

Fig. 9
Fig. 9

2 ml of water dropped onto a plastic surface (top) and a glass surface with the plastic underneath (bottom), both lit using Band A. Note that the bright spots are specular highlights.

Fig. 10
Fig. 10

First sample group, top row: granite tile, terracotta tile; middle row: aluminium, plastic; bottom row: cotton. Training regions are outlined by rectangles.

Fig. 11
Fig. 11

Scatter plots of the test samples, dry pixels plotted in red (online), wet pixels in green (online).

Fig. 12
Fig. 12

Segmentation results for sample group 1. Clockwise: granite tile, terracotta tile, plastic, and aluminium. The algorithm failed completely for the cotton sample (not shown).

Fig. 13
Fig. 13

Data set 2, clockwise: leaf, textured plastic plates, glossy paper, and varnished wood.

Fig. 14
Fig. 14

False detection of water on grapes (top) and the grapes lit using Band A (bottom).

Fig. 15
Fig. 15

Discriminating between water and organic solvents. The regions of the image identified as being wet are shown with hatching overlaid.

Tables (1)

Tables Icon

Table 1 Accuracy of Two Linear Classifiers, One Based on the A and B Bands, the Other on the A, B, and C Bands

Metrics