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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics


  • Editor: Gregory W. Faris
  • Vol. 3, Iss. 11 — Oct. 22, 2008

Improving the performance of computer color matching procedures

A. Karbasi, S. Moradian, and S. Asiaban  »View Author Affiliations

JOSA A, Vol. 25, Issue 9, pp. 2251-2262 (2008)

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A premise was set up entailing the possibility of a synergistical combination of advantages of spectrophotometric and colorimetric matching procedures. Attempts were therefore made to test the performances of fifteen matching procedures, all based on the Kubelka–Munk theory, including two procedures utilizing the fundamental color stimulus R FCS of the spectral decomposition theory. Color differences CIE Δ E 00 as well as concentration differences Δ C AVE were used to theoretically rank the fifteen color matching procedures. Results showed that procedures based on R FCS were superior in accurately predicting colors and concentrations. Additionally, the metameric black component R MB of the decomposition theory also showed promise in predicting degrees of metamerism. This preliminary study, therefore, provides evidence for the premise of this investigation.

© 2008 Optical Society of America

OCIS Codes
(330.1690) Vision, color, and visual optics : Color
(330.1715) Vision, color, and visual optics : Color, rendering and metamerism

ToC Category:
Vision, Color, and Visual Optics

Original Manuscript: November 21, 2007
Revised Manuscript: May 7, 2008
Manuscript Accepted: June 26, 2008
Published: August 14, 2008

Virtual Issues
Vol. 3, Iss. 11 Virtual Journal for Biomedical Optics

A. Karbasi, S. Moradian, and S. Asiaban, "Improving the performance of computer color matching procedures," J. Opt. Soc. Am. A 25, 2251-2262 (2008)

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  1. J. H. Nobbs, “Kubelka-Munk theory and the prediction of reflectance,” Rev. Prog. Color. Relat. Top. 15, 66-75 (1985). [CrossRef]
  2. P. Kubelka and F. Munk, “Ein beitrag zur optik der farbanstriche (An Article on Optics of Paint Layers),” Z. Tech. Phys. (Leipzig) 12, 593-601 (1931), see also www.graphics.cornell.edu/~westin/pubs/kubelka.pdf.
  3. P. Kubelka, “New contributions to the optics of intensely light scattering materials. Part I,” J. Opt. Soc. Am. 38, 448-457 (1948). [CrossRef] [PubMed]
  4. S. Chandrasekhar, Radiative Transfer (Oxford U. Press, 1950).
  5. D. B. Judd and G. Wyszecki, Color in Business, Science and Industry (Wiley, 1975).
  6. F. W. Billmeyer, Jr., R. L. Abrams, and J. G. Davidson, “Predicted reflectance and color of paint films by Kubelka-Munk analysis, I. Turbid medium theory,” J. Paint Technol. 45, 23-30 (1973).
  7. F. W. Billmeyer, Jr., R. L. Abrams, and J. G. Davidson, “Predicted reflectance and color of paint films by Kubelka-Munk analysis, II. Performance tests,” J. Paint Technol. 45, 30-37 (1973).
  8. R. S. Berns and M. Mohammadi, “Single-constant simplification of Kubelka-Munk turbid-media theory for paint systems--A review,” Color Res. Appl. 32, 201-207 (2007). [CrossRef]
  9. R. S. Berns, Billmeyer and Saltzman's Principles of Color Technology, 3rd ed. (Wiley-Interscience, 2000).
  10. B. Philips-Invernizzi, D. Dupont, and C. Caze, “Bibliographical review for reflectance of diffusing media,” Opt. Eng. (Bellingham) 40, 1082-1092 (2001). [CrossRef]
  11. R. McDonald, “Computer match prediction--dyes,” in Colour Physics for Industry, R.McDonald, ed. (Society of Dyers and Colourists, 1997), pp. 209-291.
  12. S. H. Amirshahi and M. T. Pailthorpe, “Applying the Kubelka-Munk equation to explain the color of blends prepared from precolored fibers,” Text. Res. J. 64, 357-364 (1994). [CrossRef]
  13. C. S. Haase and G. W. Meyer, “Modeling pigmented materials for realistic image synthesis,” ACM Trans. Graphics 11, 305-332 (1992). [CrossRef]
  14. E. Allen, “Basic equations used in computer color matching,” J. Opt. Soc. Am. 56, 1256-1259 (1966). [CrossRef]
  15. R. S. Berns, “A generic approach to color modeling,” Color Res. Appl. 22, 318-325 (1997). [CrossRef]
  16. H. R. Kang, “Kubelka-Munk modeling of ink jet ink mixing,” J. Imaging Technol. 17, 76-83 (1991).
  17. D. Y. Tzeng and R. S. Berns, “Spectral-based ink selection for multiple-ink printing I. Colorant estimation of original objects,” in Proceedings of 6th IS&T/SID Color Imaging Conference, (Society for Imaging Science & Technology, 1998), pp. 106-111.
  18. D. Y. Tzeng and R. S. Berns, “Spectral-based ink selection for multiple-ink printing II. Optimal ink selection,” in Proceedings of 7th IS&T/SID Color Imaging Conference, (Society for Imaging Science & Technology, 1999), pp. 182-187.
  19. J. L. Saunderson, “Calculation of the color of pigmented plastics,” J. Opt. Soc. Am. 32, 727-736 (1942). [CrossRef]
  20. J. H. Nobbs, “Colour-match prediction for pigmented materials,” in Colour Physics for Industry, R.McDonald, ed. (Society of Dyers and Colorists, 1997), pp. 292-372.
  21. I. Ariño, U. Kleist, and M. Rigdah, “Color of pigmented plastics--measurements and predictions,” Polym. Eng. Sci. 44, 141-152 (2004). [CrossRef]
  22. J. C. Ragain, Jr., and W. M. Johnston, “Accuracy of Kubelka-Munk reflectance theory applied to human dentin and enamel,” J. Dent. Res. 80, 449-452 (2001). [CrossRef] [PubMed]
  23. E. Allen, “Basic equations used in computer color matching, II. Tristimulus match,” J. Opt. Soc. Am. 64, 991-993 (1974). [CrossRef]
  24. B. Sluban, “Comparison of colorimetric and spectrophotometric algorithms for computer match prediction,” Color Res. Appl. 18, 74-79 (1993). [CrossRef]
  25. E. Allen, “Colorant formulation and shading,” in Optical Radiation Measurements, Vol. 2, Color Measurement, F.Grum and C.J.Bartleson, eds. (Academic, 1980), pp. 289-336.
  26. A. Kumar and R. Choudhury, Modern Concepts of Color and Appearance (Science Publishers Inc., 2000).
  27. R. H. Park and E. I. Stearns, “Spectrophotometric formulation,” J. Opt. Soc. Am. 4, 112-113 (1944). [CrossRef]
  28. P. H. McGinnis, “Spectrophotometric color matching with the least square technique,” Col. Eng. 5, 22-27 (1967).
  29. N. Ohta and H. Urabe, “Spectral color matching by means of minimax approximation,” Appl. Phys. Lett. 11, 2551-2553 (1972).
  30. E. Walowit, C. J. McCarthy, and R. S. Berns, “Spectrophotometric color matching based on two-constant Kubelka-Munk theory,” Color Res. Appl. 13, 358-362 (1988). [CrossRef]
  31. D. W. Marquardet, “An algorithm for least square estimation of non linear parameters,” SIAM J. Appl. Math. 11, 431-441 (1963). [CrossRef]
  32. B. Sluban and O. Šauperl, “Least metameric recipe formulation,” Croat. Chem. Acta 76, 161-166 (2003).
  33. R. K. Winey, “Computer color matching with the aid of visual technique,” Color Res. Appl. 3, 165-167 (1978). [CrossRef]
  34. G. Wyszecki, “Valenzmetrische untersuchung des zusammen-hanges zwischen normaler und anomaler Trichromasie (Psychlogical investigation of the relation between normal and abnormal trichromatic vision),” Die Far. 2, 39-52 (1953).
  35. J. B. Cohen and W. E. Kappauf, “Metameric color stimuli, fundamental metamers, and Wyszecki's metameric black,” Austral. J. Earth. Sci. 95, 537-564 (1982).
  36. J. B. Cohen and W. E. Kappauf, “Color mixture and fundamental metamers: theory, algebra, geometry, application,” Am. J. Psychol. 98, 171-259 (1985). [CrossRef]
  37. H. S. Fairman, “Correction using parametric decomposition,” Color Res. Appl. 12, 261-265 (1987). [CrossRef]
  38. R. A. Charvat, Coloring of Plastics: Fundamentals (Wiley-Interscience, 2004).
  39. R. M. Harris, Coloring Technology for Plastics (Plastics Design Library, 1999).
  40. H. G. Völz, Industrial Color Testing--Fundamentals and Techniques (VCH Weinheim, 2001). [CrossRef]
  41. E. Allen, “Advances in colorant formulation and shading,” in Proceedings of AIC Color 77, F.W.Billmeyer, Jr., and G.Wyszecki, eds. (International Colour Association, 1978), pp 153-179.
  42. M. R. Luo, G. Cui, and B. Rigg, “The development of the CIE 2000 colour-difference formula: CIEDE 2000,” Color Res. Appl. 25, 340-350 (2001). [CrossRef]
  43. S. Moradian and B. Rigg, “The quantification of metamerism,” J. Soc. Dyers Colour. 103, 209-213 (1987). [CrossRef]
  44. F. H. Imai, M. R. Rosen, and R. S. Berns, “Comparative study of metrics for spectral match quality,” in Proceedings of CGIV 2002, C.Fernandez-Maloigne, ed. (IEEE Computer Society, 2002) pp. 492-496.
  45. M. A. López-Álvarez, J. Hernández-Andrés, E. M. Valero, and J. L. Nieves, “Colorimetric and spectral combined metric for the optimization of multispectral systems,” in Proceedings of AIC Colour 05, J.Romero, ed. (International Colour Association, 2005), pp. 1685-1688.
  46. F. Ameri, S. Moradian, M. Amani Tehran, and K. Faez, “The use of fundamental color stimulus to improve the performance of artificial neural network color match prediction systems,” Iran. J. Chem. and Chem. Eng. 24, 53-61 (2005).
  47. A. Karbasi, S. Moradian, and S. Asiaban, “The use of two constant Kubelka-Munk theory in spectrophotometric color matching,” in Proceedings of ICE2007, P.Ziegler, ed. (International Coatings Expo, 2007).
  48. R. Kuehni, Computer Color Formulation (Lexington Books, 1975).
  49. H. Schmid and D. Strocka, “Adaptation of computer colour matching to practical requirements,” in Proceedings of XIth FATIPEC, fatipec.com (1972), pp. 163-170.
  50. F. Ameri, S. Moradian, M. A. Tehran, and K. Faez, “Use of transformed reflectance functions for neural network color match prediction systems,” Ind. J. Fib. Tex. Res. 31, 439-443 (2006).
  51. C. L. Lawson and R. J. Hanson, Solving Least Squares Problems (Society for Industrial and Applied Mathematics, 1995). [CrossRef]

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