An Approach Fractal and Analysis of Variogram for Edge Detection of Biomedical Images

  • L. Hamami
  • N. Lassouaoui
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2085)


In this work, we study a fractal approach of edge detection. This approach is based on the evaluation of the local fractal dimension (in every pixel of the image) by using Gabor filtering. Gabor Filters use several parameters, as: radial frequency ρ and angular frequency θ. As we will see the choice of these parameters influence directly on the edge detection. Our contribution is using a mathematical tool said variogram that is going to guide us in the selection of the angular frequency θ. The method is based on exploitation of local indications that permits to affirm the existence of edge in an image on a direction θ. Results of edge detection are better since there is extraction in privileged directions of the image.

Key words

Gabor filtering local fractal dimension variogram edge detection biomedical images 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    C.J. Burdett and M. Desai, Localized fractal dimension measurement in digital mammographic images, SPIE, 2094, 1993, 141–151.CrossRefGoogle Scholar
  2. [2]
    J.M. Blackledge and E. Fowler, Fractal Dimension Segmentation of Synthetic Aperture Radar Images, Image Processing and its Applications, 1992, 445–449.Google Scholar
  3. [3]
    S. Soltane, J. Claude Angue, FrSélection d’opérateurs directionnels basée sur les variogrammes, Revue Internationale des Technologies Avancées, 11, 1999, 14–22.Google Scholar
  4. [4]
    B. Mandelbrot, Fractals Form, Chance, And Dimension, W.H. Freeman And Company, 1977.Google Scholar
  5. [5]
    Yuxin Liu and Yandan Li, Image Feature Extraction and Segmentation using Fractal Dimension, IEEE Information Communications and Signal Processing, 1997, 975–979.Google Scholar
  6. [6]
    A. Arneodo, F. Argoul, E. Bacry, J. Elezgaray, J-F. Muzy, Ondelettes, multifractales et turbulences de l’ADN aux croissances cristallines, Arts et Sciences, 1995.Google Scholar
  7. [7]
    Ph. Bolon, J-M. Chassery, J-P. Cocquerez, D. Demigny, C. Graffigne, A. Montanvert, S. Philipp, R. Zéboudj, J. Zérubia, Analyse d’images: filtrage et segmentation, Masson, 1995.Google Scholar
  8. [8]
    R.C. Gonzalez, Digital Image Processing, 2ind Edition, Addison-Wesley, 1987.Google Scholar
  9. [9]
    B. Mandelbrot, Les objets fractals, Flammarion, 1995.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • L. Hamami
    • 1
  • N. Lassouaoui
    • 1
  1. 1.Polytechnic National School Department of electronicsEl-Harrach Alger

Personalised recommendations