Contribution to the colour segmentation by means of an algorithm which reduces the CCDs saturation problems

  • Jordi Regincós Isern
  • Joan Batlle Grabulosa
Poster Session A: Color & Texture, Enhancement, Image Analysis & Pattern Recognition, Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)


Sometimes, the results provided by colour image processing systems are not accurate enough due to the physical process of image formation. One of that problems is colour clipping, which appear when at least one of the sensor components is saturated. We propose a method to recover the chromatic information of those pixels on which colour has been clipped. The chromatic correction method is based on the fact that some chromatic characteristics are invariant to the uniform scaling of the three RGB components. In this paper we present this method and one study of the chromatic components to which it can be applied.

Key Words

Colour Clipping Colour recovering Colour segmentation 


  1. 1.
    M. Barni, V. Cappellini, and A. Mecocci. A vision system for automatic inspection of meat quality. 8th Int. Conf. on Image Analysis and Processing, number 974 in Lecture Notes in Computer Science, pages 748–753, 1995.Google Scholar
  2. 2.
    T. Carron and P. Lambert. Color edge detector using jointly hue, saturation and intensity. IEEE Int. Conf. on Image Processing, vol. 3, pages 977–981, 1994.Google Scholar
  3. 3.
    Ron Gershon. Aspects of perception and computation in color vision. Computer Vision, Graphics and Image Processing, 32:244–277, 1985.Google Scholar
  4. 4.
    G.H. Joblove and D. Greenberg. Color spaces for computer graphics. Computer & Graphics, 12:12–19, 1978.Google Scholar
  5. 5.
    Gudrun J. Klinker, Steven A. Shafer, and Takeo Kanade. The measurement of highlights in color images. International Journal of Computer Vision, 2(1):7–32, June 1988.Google Scholar
  6. 6.
    Quang-Tuan Luong. Color in computer vision. In L.F. Pau C.H. Chen and P.S.P. Wang, editors, Handbook of Pattern Recognition and Computer Vision, pages 311–368. World Scientific Publishing Company, 1993.Google Scholar
  7. 7.
    R. Nevatia. A color edge detector and its use in scene segmentation. IEEE Transactions on Systems, Man and Cybernetics, 7(11):820–826, 1977.Google Scholar
  8. 8.
    Carol L. Novak, Steven A. Shafer, and Reg G. Willson. Obtaining accurate color images for machine vision research. In Proc. of the Conference on Perceiving, Measuring and Using Color. SPIE, Volume 1250, February 1990.Google Scholar
  9. 9.
    Frank A. Perez and Christof Koch. Toward color image segmentation in analog VLSI: Algorithm and hardware. International Journal of Computer Vision, 12(1):17–42, February 1994.Google Scholar
  10. 10.
    Jordi Regincós and Joan Batlle. A system to reduce the effect of CCD saturation. In Proc. of the IEEE International Conference on Image Processing, volume I, pages 1001–1004, 1996.Google Scholar
  11. 11.
    S.A. Shafer. Using color to separate reflection components. Color Research and Application, 10(4):210–218, 1985.Google Scholar
  12. 12.
    A.R. Smith. Color gamut transform pairs. Computer & Graphics, 12(3):12–19, 1978.Google Scholar
  13. 13.
    J. N. Tenenbaum. An interactive facility for scene analysis research. Technical Note 87, Artificial Intelligence Center, Stanford Research Institute, 1974.Google Scholar
  14. 14.
    Günter Wyszecki and W.S. Stiles. Color Science (Concepts and Methods, Quantitative Data and Formulae). John Wiley & Sons, 1982.Google Scholar
  15. 15.
    Daisuke Yagi, Kejichi Abe, and Hiromasa Nakatami. Segmentation of color aerial photographs using HSV color models. In MVA'92 Workshop. IAPR, 1992.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Jordi Regincós Isern
    • 1
  • Joan Batlle Grabulosa
    • 1
  1. 1.Institut d'Informàtica i AplicacionsUniversitat de GironaGironaSpain

Personalised recommendations