An automatic system for urban road extraction from satellite and aerial images

  • Authors:

  • S. Idbraim;D. Mammass;D. Aboutajdine;D. Ducrot

  • Affiliations:

  • GSCM-LRIT laboratory, Faculty of Science, University Mohammed V Agdal, Rabat, Morocco and IRF-SIC Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco;IRF-SIC Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco;GSCM-LRIT laboratory, Faculty of Science, University Mohammed V Agdal, Rabat, Morocco;CESBIO, University Paul Sabatier-Toulouse, France

  • Venue:
  • WSEAS Transactions on Signal Processing
  • Year:
  • 2008

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Abstract

we present in this paper an automatic system of urban road extraction from satellite and aerial imagery. Our approach is based on an adaptive directional filtering and a watershed segmentation. The first stage consists of an automatic procedure which adapts filtering of each block band to the dominant direction(s) of roads. The choice of the dominant direction(s) is made from a criterion based on the calculation of a factor of direction of detection. The second stage is based on watershed algorithm applied to a Shen-Castan gradient image. This process provides a decision map allowing correcting the errors of the first stage. A ratio of surface on perimeter is used to distinguish among all segments of the image those representing probably roads. Finally, in order to avoid gaps between pieces of roads, the resulting image follows a treatment, based on proximity and colinearity, for linking segments. The proposed approach is tested on common scenes of Landsat ETM+ and aerial imagery of the city of Agadir in Morocco. The experimental results show satisfactory values of completeness and correctness and are very prominsing.