OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 17, Iss. 11 — Nov. 1, 2000
  • pp: 1952–1961

Shadow-invariant classification for scenes illuminated by daylight

John A. Marchant and Christine M. Onyango  »View Author Affiliations


JOSA A, Vol. 17, Issue 11, pp. 1952-1961 (2000)
http://dx.doi.org/10.1364/JOSAA.17.001952


View Full Text Article

Enhanced HTML    Acrobat PDF (288 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

A physics-based method for shadow compensation in scenes illuminated by daylight is proposed. If the daylight is represented by a simplified form of the blackbody law and the camera filters are of infinitely narrow bandwidth, the relationship between red/blue (rm) and green/blue (gm) ratios as the blackbody’s temperature changes is a simple power law where the exponent is independent of the surface reflectivity. When the CIE daylight model is used instead of the blackbody and finite bandwidths for the camera are assumed, it is shown that the power law still holds with a slight change to the exponent. This means that images can be transformed into a map of rm/gmA and then thresholded to yield a shadow-independent classification. Exponent A can be precalculated from the CIE daylight model and the camera filter characteristics. Results are shown for four outdoor images that contain sunny and shadowed parts with vegetation and background. It is shown that the gray-level distributions of the pixels in the transformed images are quite similar for a given component whether or not it is in shadow. The transformation leads to bimodal histograms from which thresholds can easily be selected to give good classifications.

© 2000 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(150.2950) Machine vision : Illumination

History
Original Manuscript: November 23, 1999
Revised Manuscript: June 14, 2000
Manuscript Accepted: June 14, 2000
Published: November 1, 2000

Citation
John A. Marchant and Christine M. Onyango, "Shadow-invariant classification for scenes illuminated by daylight," J. Opt. Soc. Am. A 17, 1952-1961 (2000)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-17-11-1952


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. G. E. Healey, S. A. Shafer, L. B. Wolff, eds., Physics-Based Vision: Principles and Practice (Jones & Bartlett, Boston, Mass., 1992).
  2. “Physics-Based Machine Vision,” feature issue, J. Opt. Soc. Am. A 11, 2922–3100 (1994). [CrossRef]
  3. R. Brivot, J. A. Marchant, “Segmentation of plants and weeds using infrared images,” Proc. Inst. Electr. Eng. 143, 118–124 (1996).
  4. T. Hague, J. A. Marchant, N. D. Tillett, “A system for plant scale husbandry,” in Proceedings of the 1st European Conference on Precision Agriculture (BIOS Scientific, Oxford, UK, 1997), pp. 635–642.
  5. N. D. Tillett, T. Hague, “Computer-vision-based hoe guidance for cereals—an initial trial,” J. Agric. Eng. Res. 74, 225–236 (1999). [CrossRef]
  6. M. S. Drew, J. Wei, Z. Li, “Illumination invariant image retrieval and video segmentation,” Pattern Recogn. 32, 1369–1388 (1999). [CrossRef]
  7. A. D. Jepson, R. Gershon, J. K. Tsotsos, “Ambient illumination and the determination of material changes,” J. Opt. Soc. Am. A 3, 1700–1707 (1986). [CrossRef] [PubMed]
  8. D. Reynard, A. Wildenberg, A. Blake, J. A. Marchant, “Learning dynamics of complex motions from image sequences,” in Proceedings of the 4th European Conference on Computer Vision (Springer, Berlin, 1996), pp. 357–368.
  9. G. L. Foresti, “Object detection and tracking in time-varying and badly illuminated outdoor environments,” Opt. Eng. 37, 2550–2564 (1998). [CrossRef]
  10. J. D. Crisman, C. E. Thorpe, “SCARF: a color vision system that tracks roads and intersections,” IEEE Trans. Rob. Autom. 9, 49–57 (1993). [CrossRef]
  11. S. Nakauchi, K. Takebe, S. Usui, “A computational model for color constancy by separating reflectance and illuminant edges within a scene,” Neural Networks 9, 1405–1415 (1996). [CrossRef] [PubMed]
  12. S. Tominaga, B. A. Wandell, “Standard surface-reflectance model and illuminant estimation,” J. Opt. Soc. Am. A 6, 576–584 (1989). [CrossRef]
  13. S. A. Shafer, “Using color to separate reflection components,” Color Res. Appl. 10, 210–218 (1985). [CrossRef]
  14. H.-C. Lee, E. J. Breneman, C. P. Schulte, “Modeling light reflection for color computer vision,” IEEE Trans. Pattern Anal. Mach. Intell. 12, 402–409 (1990). [CrossRef]
  15. G. Brelstaff, A. Blake, “Detecting specular reflections using Lambertian constraints,” in Proceedings of the 2nd International Conference on Computer Vision (Institute of Electrical and Electronics Engineers, New York, 1988), pp. 297–302.
  16. H. C. Lee, “Method for computing the scene-illuminant chromaticity from specular highlights,” J. Opt. Soc. Am. A 3, 1694–1699 (1986). [CrossRef] [PubMed]
  17. G. J. Klinker, S. A. Shafer, T. Kanade, “The measurement of highlights in color images,” Int. J. Comput. Vision. 2, 7–32 (1988). [CrossRef]
  18. S. J. Maas, J. R. Dunlap, “Reflectance, transmittance, and absorptance of light by normal, etiolated, and albino corn leaves,” Agron. J. 81, 105–110 (1989). [CrossRef]
  19. C. A. Shull, “A spectrophotometric study of plant reflection of light from leaf surfaces,” Bot. Gaz. 87, 583–607 (1929). [CrossRef]
  20. W. D. Billings, R. J. Morris, “Reflection of visible and infrared radiation from leaves of different ecological groups,” Am. J. Bot. 38, 327–331 (1951). [CrossRef]
  21. J. T. Wooley, “Reflectance and transmittance of light by leaves,” Plant Physiol. 47, 656–662 (1971). [CrossRef]
  22. E. A. Walter-Shea, J. M. Norman, “Leaf optical properties,” in Photon-Vegetation Interactions (Springer-Verlag, Berlin, 1991), pp. 230–250.
  23. A. W. Hooper, G. O. Harries, B. Ambler, “A photoelectric sensor for distinguishing between plant material and soil,” J. Agric. Eng. Res. 21, 145–155 (1976). [CrossRef]
  24. G. Wyszecki, W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed. (Wiley, New York, 1982).
  25. Commission Internationale de L’Eclairage (CIE), “Method of measuring and specifying colour rendering properties of light sources,” (CIE, Paris, 1995).
  26. Commission Internationale de L’Eclairage (CIE) “Colorimetry,” Tech. Rep.2nd ed. (CIE, Paris, 1986).
  27. D. B. Judd, D. L. MacAdam, G. W. Wyszecki, “Spectral distribution of typical daylight as a function of correlated color temperature,” J. Opt. Soc. Am. 54, 1031–1040 (1964). [CrossRef]
  28. G. D. Finlayson, M. S. Drew, B. F. Funt, “Color constancy: generalized diagonal transforms suffice,” J. Opt. Soc. Am. A 11, 3011–3019 (1994). [CrossRef]
  29. G. West, M. H. Brill, “Necessary and sufficient conditions for von Kries chromatic adaptation to give color constancy,” J. Math. Biol. 15, 249–258 (1982). [CrossRef] [PubMed]
  30. K. Barnard, G. Finlayson, B. Funt, “Color constancy for scenes with varying illumination,” Comput. Vision Image Understand. 65, 311–321 (1997). [CrossRef]
  31. G. D. Finlayson, M. S. Drew, B. F. Funt, “Spectral sharpening: sensor transformations for improved color constancy,” J. Opt. Soc. Am. A 11, 1553–1563 (1994). [CrossRef]
  32. S. Tominaga, “Multichannel vision system for estimating surface and illumination functions,” J. Opt. Soc. Am. A 13, 2163–2173 (1996). [CrossRef]
  33. J. D. E. Beynon, D. R. Lamb, eds., Charge Coupled Devices and Their Application (McGraw-Hill, London, 1980).
  34. S. Perrin, T. Redarce, “CCD camera modelling and simulation,” J. Intell. Robot. Syst. 17, 309–325 (1996). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited