OSA's Digital Library

Applied Optics

Applied Optics


  • Vol. 43, Iss. 9 — Mar. 19, 2004
  • pp: 1880–1891

Spectral-reflectance linear models for optical color-pattern recognition

Juan L. Nieves, Javier Hernández-Andrés, Eva Valero, and Javier Romero  »View Author Affiliations

Applied Optics, Vol. 43, Issue 9, pp. 1880-1891 (2004)

View Full Text Article

Enhanced HTML    Acrobat PDF (2057 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



We propose a new method of color-pattern recognition by optical correlation that uses a linear description of spectral reflectance functions and the spectral power distribution of illuminants that contains few parameters. We report on a method of preprocessing color input scenes in which the spectral functions are derived from linear models based on principal-component analysis. This multichannel algorithm transforms the red-green-blue (RGB) components into a new set of components that permit a generalization of the matched filter operations that are usually applied in optical pattern recognition with more-stable results under changes in illumination in the source images. The correlation is made in the subspace spanned by the coefficients that describe all reflectances according to a suitable basis for linear representation. First we illustrate the method in a control experiment in which the scenes are captured under known conditions of illumination. The discrimination capability of the algorithm improves upon the conventional RGB multichannel decomposition used in optical correlators when scenes are captured under different illuminant conditions and is slightly better than color recognition based on uniform color spaces (e.g., the CIELab system). Then we test the coefficient method in situations in which the target is captured under a reference illuminant and the scene that contains the target under an unknown spectrally different illuminant. We show that the method prevents false alarms caused by changes in the illuminant and that only two coefficients suffice to discriminate polychromatic objects.

© 2004 Optical Society of America

OCIS Codes
(100.4550) Image processing : Correlators
(100.5010) Image processing : Pattern recognition
(330.1690) Vision, color, and visual optics : Color

Original Manuscript: May 30, 2003
Revised Manuscript: September 16, 2003
Published: March 20, 2004

Juan L. Nieves, Javier Hernández-Andrés, Eva Valero, and Javier Romero, "Spectral-reflectance linear models for optical color-pattern recognition," Appl. Opt. 43, 1880-1891 (2004)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. F. T. S. Yu, “Color image recognition by spectral-spatial matched filtering,” Opt. Eng. 23, 690–695 (1984). [CrossRef]
  2. E. Badiqué, Y. Koyima, N. Ohyama, J. Tsujiuchi, T. Honda, “Color image correlation,” Opt. Commun. 61, 181–186 (1987). [CrossRef]
  3. M. S. Millán, J. Campos, C. Ferreira, M. J. Yzuel, “Matched filter and phase only filter performance in colour image recognition,” Opt. Commun. 73, 277–284 (1989). [CrossRef]
  4. M. S. Millán, M. J. Yzuel, J. Campos, C. Ferreira, “Different strategies in optical recognition of polychromatic images,” Appl. Opt. 31, 2560–2567 (1992). [CrossRef] [PubMed]
  5. M.-L. Hsieh, K. Y. Hsu, H. Zhai, “Color image recognition by use of a joint transform correlator of three liquid-crystal televisions,” Appl. Opt. 41, 1500–1504 (2002). [CrossRef] [PubMed]
  6. I. Moreno, V. Kober, V. Lashin, J. Campos, L. P. Yaroslavsky, M. J. Yzuel, “Color pattern recognition with circular component whitening,” Opt. Lett. 21, 499–500 (1992).
  7. M. S. Millán, M. Corbalán, J. Romero, M. J. Yzuel, “Optical pattern recognition based on color vision models,” Opt. Lett. 20, 1722–1724 (1995). [CrossRef] [PubMed]
  8. A. Fares, P. García-Martínez, C. Ferreira, M. Hamdi, A. Bouzid, “Multi-channel chromatic transformations for nonlinear color pattern recognition,” Opt. Commun. 203, 255–261 (2002). [CrossRef]
  9. J. Nicolas, M. J. Yzuel, J. Campos, “Colour pattern recognition by three-dimensional correlation,” Opt. Commun. 184, 335–343 (2000). [CrossRef]
  10. J. Nicolas, I. Moreno, J. Campos, M. J. Yzuel, “Phase-only filtering on the three-dimensional Fourier spectrum of color images,” Appl. Opt. 42, 1426–1433 (2003). [CrossRef] [PubMed]
  11. J. Nicolas, C. Iemmi, J. Campos, M. J. Yzuel, “Optical encoding of color three-dimensional correlation,” Opt. Commun. 209, 35–43 (2002). [CrossRef]
  12. M. Corbalán, M. S. Millán, M. J. Yzuel, “Color measurement in standard CIELAB coordinates using a 3CCD camera: correction for the influence of the light source,” Opt. Eng. 39, 1470–1476 (2000). [CrossRef]
  13. M. Corbalán, M. S. Millán, M. J. Yzuel, “Color pattern recognition with CIELAB coordinates,” Opt. Eng. 41, 130–138 (2002). [CrossRef]
  14. M. J. Swain, D. H. Ballard, “Color indexing,” Int. J. Comput. Vision 7, 11–32 (1991). [CrossRef]
  15. B. V. Funt, G. D. Finlayson, “Color constant color indexing,” IEEE Trans. Pattern Anal. Mach. Intell. 17, 522–529 (1995). [CrossRef]
  16. G. D. Finlayson, S. D. Hordley, P. M. Hubel, “Color by correlation: a simple, unifying framework for color constancy,” IEEE Trans. Pattern Anal. Mach. Intell. 23, 1209–1221 (2001). [CrossRef]
  17. L. Wang, G. Healey, “Using multiband filtered energy matrices for recognition and illumination correction,” Opt. Eng. 37, 2668–2674 (1998). [CrossRef]
  18. L. T. Maloney, B. Wandell, “Color constancy: a method for recovering surface spectral reflectance,” J. Opt. Soc. Am. A 3, 23–33 (1986). [CrossRef]
  19. A. García-Beltrán, J. L. Nieves, J. Hernández-Andrés, J. Romero, “Linear bases for spectral reflectance functions of acrylic paints,” Color Res. Appl. 23, 39–45 (1998). [CrossRef]
  20. J. P. S. Parkinnen, J. Hallikainen, T. Jaaskelainen, “Characteristic spectra of Munsell colors,” J. Opt. Soc. Am. A 6, 318–322 (1989). [CrossRef]
  21. M. J. Vrhel, R. Gershon, L. S. Iwan, “Measurements and analysis of object reflectance spectra,” Color Res. Appl. 19, 4–9 (1994).
  22. E. R. Dixon, “Spectral distribution of Australian daylight,” J. Opt. Soc. Am. 68, 437–450 (1978). [CrossRef]
  23. J. Romero, A. García-Beltrán, J. Hernández-Andrés, “Linear bases for representation of natural and artificial illuminants,” J. Opt. Soc. Am. A 14, 1007–1014 (1997). [CrossRef]
  24. J. Hernández-Andrés, J. Romero, J. L. Nieves, R. L. Lee, “Color and spectral analysis of daylight in southern Europe,” J. Opt. Soc. Am. A 18, 1325–1335 (2001). [CrossRef]
  25. G. Buchsbaum, “A spatial processor model for object colour perception,” J. Franklin Inst. 310, 1–26 (1980). [CrossRef]
  26. M. D’Zmura, G. Iverson, “Color constancy. I. Basic theory of two-stage linear recovery of spectral descriptions for lights and surfaces,” J. Opt. Soc. Am. A 10, 2148–2165 (1993). [CrossRef]
  27. M. D’Zmura, G. Iverson, “Color constancy. II. Results from two-stage linear recovery of spectral descriptions for lights and surfaces,” J. Opt. Soc. Am. A 10, 2166–2180 (1993). [CrossRef]
  28. B. V. Funt, M. S. Drew, J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vision 6, 5–24 (1991). [CrossRef]
  29. See Ref. 13, pp. 1472–1475, for full details about the derivation of the matrices that allow the computation of CIELab coordinates from RGB values.
  30. J. Y. Hardeberg, “Acquisition and reproduction of color images: colorimetric and multispectral approaches,” Ph.D. dissertation (Ecole Nationale Supérieure des Télécommunications, Paris, 1999), pp. 157–174.
  31. K. Barnard, L. Martin, B. Funt, A. Coath, “A data set for color research,” Color Res. Appl. 27, 148–152 (2002). [CrossRef]
  32. F. H. Imai, M. R. Rosen, R. S. Berns, “Comparative study of metrics for spectral match quality,” in Proceedings of the First European Conference on Colour in Graphics, Imaging, and Vision (Society for Imaging Science and Technology, Springfield, Va., 2002), pp. 492–496.

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