Fast Color-Weakness Compensation with Discrimination Threshold Matching

  • Rika Mochizuki
  • Satoshi Oshima
  • Jinhui Chao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6626)


We present a method to compensate color-weak vision along the confusion lines, based on matching between discrimination thresholds of the color-weak observer and of color-normals. The compensation and simulation map preserve color-differences of every pair of colors between color-normals and the color-weak observer. We developed an explicit formula for compensation and simulation of color-weak vision in closed form. The method is easy to implement and fast.


Color Space Riemann Space Discrimination Threshold Color Distribution Color Stimulus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Brettel, H., Vienot, F., Mollon, J.D.: Computerized simulation of color appearance for dichromats. Journal of Optical Society of America 14(10), 2647–2655 (1997)CrossRefGoogle Scholar
  2. 2.
    Ichikawa, M., Tanaka, K., Kondo, S., Hiroshima, K., Ichikawa, K., Tanabe, S., Fukami, K.: Preliminary Study on Color Modification for Still Images to Realize Barrier-Free Color Vision. In: Proc. IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 (2004)Google Scholar
  3. 3.
    Troiano, L., Birtolo, C., Italiane, P.: Adapting Palettes to Color Vision Deficiencies by Genetic Algorithm. In: Proc. 10th Genetic and Evolutionary Computation Conference in CD-ROM (2008)Google Scholar
  4. 4.
    MacAdam, D.L.: Visual sensitivities to color differences in daylight. Journal of Optical Society of America 32(5), 247–274 (1942)CrossRefGoogle Scholar
  5. 5.
    Wyszecki, G., Stiles, W.S.: Color Science, 2nd edn. Wiley Classics Library (2000)Google Scholar
  6. 6.
    do Carmo, M.P.: Riemannian Geometry. Birkhauser, Basel (1992)CrossRefzbMATHGoogle Scholar
  7. 7.
    Chao, J., Osugi, I., Suzuki, M.: On definitions and construction of uniform color space. In: Proceedings of CGIV 2004, The Second European Conference on Colour in Graphics, Imaging and Vision, Aachen, Germany, April 5-8, pp. 55–60 (2004)Google Scholar
  8. 8.
    Regan, B.C., Reffin, J.P., Mollon, J.D.: Luminance noise and the rapid determination of discrimination ellipses in colour deficiency. Vision Research 34(10), 1279–1299 (1994)CrossRefGoogle Scholar
  9. 9.
    Mochizuki, R., Nakamura, T., Chao, J., Lenz, R.: Color-weak correction by discrimination threshold matching. In: Proceedings of CGIV 2008, 4th European Conference on Color in Graphics, Imaging, and Vision, Terrassa, Spain, June 9-13, pp. 208–213 (2008)Google Scholar
  10. 10.
    Chao, J., Lenz, R., Matsumoto, D., Nakamura, T.: Riemann geometry for color characterization and mapping. In: Proceedings of CGIV 2008, Proceedings of 4th European Conference on Color in Graphics, Imaging, and Vision, June 9-13, pp. 277–282 (2008)Google Scholar
  11. 11.
    Ohshima, S., Mochizuki, R., Chao, J., Lenz, R.: Color reproduction using riemann normal coordinates. In: Trémeau, A., Schettini, R., Tominaga, S. (eds.) CCIW 2009. LNCS, vol. 5646, pp. 140–149. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rika Mochizuki
    • 1
    • 2
  • Satoshi Oshima
    • 2
  • Jinhui Chao
    • 2
  1. 1.NTT Cyber Solutions LaboratoriesYokosuka-shiJapan
  2. 2.Chuo UniversityBunkyo-kuJapan

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