Cross-media color matching using neural networks

  • E. Boldrin
  • R. Schettini
Session 4: Color & Texture
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)


Cross-media color reproduction is receiving a great deal of attention as a result of the increasing availability of color devices. A practical approach to accurate color reproduction, integrating colorimetric and interactive methods by means of feed-forward neural networks trained by back-propagation, is proposed. Experimental results confirming the feasibility of this approach are reported.


Membership Function Color Correction Color Appearance Color Range Color Scanner 
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.
    P.J. Alessi “CIE guidelines for coordinate research on evaluation of colour appearance models for reflection print and self-luminous display image comparison” Color Research and Application Vol. 19, pp. 48–58, 1994.Google Scholar
  2. 2.
    E Binaghi, I Gagliardi, R. Schettini “Image retrieval using fuzzy evaluation of color similarity” International Journal of Pattern Recognition and Artificial Intelligence, Vol. 8, pp. 945–968, 1994.Google Scholar
  3. 3.
    E. Boldrin, P. Campadelli, R. Schettini “Effective and efficient mapping of color appearance” Color Research and Application, 1997 (in print).Google Scholar
  4. 4.
    J. Hertz, A. Krogh, R.G. Palmer “Introduction to the theory of neural computing” Addison-Wesley, New York, Vol. 1, pp. 115–162, 1991.Google Scholar
  5. 5.
    B.K.P. Horn (1984) Exact Reproduction of Colored Images, Computer Vision, Graphics and Image Processing, Vol. 26, pp. 135–167.Google Scholar
  6. 6.
    R.G.W. Hunt “Revised colour-appearance model for related and unrelated colours” Color Research and Application, Vol. 16, pp. 146–165, 1991.Google Scholar
  7. 7.
    K. Kanamori, H. Kotera “A Method for Selective Color Control In Perceptual Color Space” Journal of Imaging Technologies, Vol. 35(5), pp. 307–316, 1991.Google Scholar
  8. 8.
    H.R. Kang P.G. Anderson “Neural network application to the color scanner and printer calibrations” Journal of Electronic Imaging, Vol. 1, pp. 25–135, 1992.Google Scholar
  9. 9.
    H. Kang “Color Scanner Calibration. Journal of Imaging and technology”, Vol. 36, 162–170, 1992.Google Scholar
  10. 10.
    N. Otha “Development of color targets for input scanner calibration” Proc. 7th Congress of the International Color Association “Colour 93”, Technical University of Budapest, Budapest (Hungary), p. 130, 1993.Google Scholar
  11. 11.
    Proc. and IS&T and SID's Second Color Imaging Conference: Color Science, Systems and Applications, 1995.Google Scholar
  12. 12.
    D.E. Rumelhart, G.E. Hinton, R.J. Williams “Learning internal representations by error propagation” In D.E. Rumelhart, J.L. McClelland Eds, Parallel distributed processing MIT Press, Cambridge (MA), Vol. 1 pp. 145–168, 1986.Google Scholar
  13. 13.
    H. Saarelma, P. Oittinen “Automatic Picture Reproduction” Graphics Art in Finland, Vol. 22(1), pp. 3–11, 1993.Google Scholar
  14. 14.
    R. Schettini, A. Della Ventura, M.T. Artese “Color Specification by Visual Interaction” The Visual Computer, Vol 9(6), pp. 143–150, 1992.Google Scholar
  15. 15.
    R. Schettini “The faithful rendition of color ranges on display, Proc. IS&T and SID's Color Imaging Conference: Transforms & Transportability of Color, Scottsdale, Arziona, pp. 160–163, 1993.Google Scholar
  16. 16.
    R. Schettini, B. Barolo, E. Boldrin “Colorimetric calibration of color scanners by back propagation” Pattern Recognition Letters, Vol. 16(10), pp. 1051–1056, 1995.Google Scholar
  17. 17.
    R. Schettini, B. Barolo, E. Boldrin “A soft color cluster editor” Image Processing and Communications, Vol. 1(1), pp. 17–32, 1995.Google Scholar
  18. 18.
    N.J.C. Strachan, P. Nesvadba e A.R. Allen “Calibration of video camera digitising system in the L*u*v* colour space” Pattern Recognition Letters, 11, 771–777, 1990.Google Scholar
  19. 19.
    G. Wyszecki e W.S. Stiles “Color science: concepts and methods, quantitative data and formulae”, Wiley, New York, 1982.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • E. Boldrin
    • 1
  • R. Schettini
    • 1
  1. 1.National Research Council (CNR)Institute of Multimedia Information Technologies (ITIM)MilanoItaly

Personalised recommendations