Graph cuts approach to MRF based linear feature extraction in satellite images

  • Authors:
  • Anesto Del-Toro-Almenares;Cosmin Mihai;Iris Vanhamel;Hichem Sahli

  • Affiliations:
  • Vrije Universiteit Brussel, Dept. of Electronics and Informatics, Brussels, Belgium and Univ. Central de Las Villas, Center for Studies on Electronics and Information Technologies, Villa Clara, Cu ...;Vrije Universiteit Brussel, Dept. of Electronics and Informatics, Brussels, Belgium;Vrije Universiteit Brussel, Dept. of Electronics and Informatics, Brussels, Belgium;Vrije Universiteit Brussel, Dept. of Electronics and Informatics, Brussels, Belgium

  • Venue:
  • CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper investigates the use of graph cuts for the minimization of an energy functional for road detection in satellite images, defined on the Bayesian MRF framework. The road identification process is modeled as a search for the optimal binary labeling of the nodes of a graph, representing a set of detected segments and possible connections among them. The optimal labeling corresponds to the configuration that minimizes an energy functional derived from a MRF probabilistic model, that introduces contextual knowledge about the shape of roads. We formulate an energy function modeling the interactions between road segments, while satisfying the regularity conditions required by the graph cuts based minimization. The obtained results show a noticeable improvement in terms of processing time, while achieving good results.