Combining SVM and Graph Matching in a Bayesian Multiple Classifier System for Image Content Recognition

  • Bertrand Le Saux
  • Horst Bunke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4109)


In this paper, we propose an approach to image content recognition that exploits the benefits of different image representations to associate meaning with images. We choose classifiers based on global appearance, scene structure and region type occurrence, and define confidence measures on their output. The resulting posterior probabilities of the classifiers are combined in a Bayesian framework. We show that this method leads to a robust and efficient system that contributes to reducing the semantic gap between low level image features and higher level image descriptions.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bertrand Le Saux
    • 1
  • Horst Bunke
    • 1
  1. 1.Institut für Informatik und Angewandte MathematikUniversity of BernBernSwitzerland

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