Vector morphological operators for colour images

  • Authors:

  • Valérie De Witte;Stefan Schulte;Mike Nachtegael;Dietrich Van der Weken;Etienne E. Kerre

  • Affiliations:

  • Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium;Department of Applied Mathematics and Computer Science, Fuzziness and Uncertainty Modelling Research Unit, Ghent University, Gent, Belgium

  • Venue:
  • ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
  • Year:
  • 2005

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Abstract

In this paper we extend the basic morphological operators dilation and erosion for grey-scale images based on the threshold approach, umbra approach and fuzzy set theory to colour images. This is realised by treating colours as vectors and defining a new vector ordering so that new colour morphological operators are presented. Here we only discuss colours represented in the RGB colour space. The colour space RGB becomes together with the new ordering and associated minimum and maximum operators a complete chain. All this can be extended to the colour spaces HSV and L*a*b*. Experimental results show that our method provides an improvement on the component-based approach of morphological operators applied to colour images. The colours in the colour images are preserved, that is, no new colours are introduced.