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An Evolutionary Approach for Ontology Driven Image Interpretation

  • Germain Forestier
  • Sébastien Derivaux
  • Cédric Wemmert
  • Pierre Gançarski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4974)

Abstract

Image mining and interpretation is a quite complex process. In this article, we propose to model expert knowledge on objects present in an image through an ontology. This ontology will be used to drive a segmentation process by an evolutionary approach. This method uses a genetic algorithm to find segmentation parameters which allow to identify in the image the objects described by the expert in the ontology. The fitness function of the genetic algorithm uses the ontology to evaluate the segmentation. This approach does not needs examples and enables to reduce the semantic gap between automatic interpretation of images and expert knowledge.

Keywords

Genetic Algorithm Segmentation Algorithm Evolutionary Approach Watershed Segmentation Automatic Interpretation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Germain Forestier
    • 1
  • Sébastien Derivaux
    • 1
  • Cédric Wemmert
    • 1
  • Pierre Gançarski
    • 1
  1. 1.LSIIT - CNRSUniversity Louis Pasteur - UMR 7005IllkirchFrance

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