On Building Omnidirectional Image Signatures Using Haar Invariant Features: Application to the Localization of Robots

  • Cyril Charron
  • Ouiddad Labbani-Igbida
  • El Mustapha Mouaddib
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)


In this paper, we present a method for producing omnidirectional image signatures that are purposed to localize a mobile robot in an office environment. To solve the problem of perceptual aliasing common to the image based recognition approaches, we choose to build signatures that greatly vary between rooms and slowly vary inside a given room. To do so, an invariant approach has been developed, based on Haar invariant integrals. It takes into account the movements the robot can do in a room and the omni image transformations thus produced. A comparison with existing methods is presented using the Fisher criterion. Our method appears to get significantly better results for place recognition and robot localization, reducing in a positive way the perceptual aliasing.


Mobile Robot Image Retrieval Invariant Feature Signature Extraction Robot Localization 
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 2006

Authors and Affiliations

  • Cyril Charron
    • 1
  • Ouiddad Labbani-Igbida
    • 1
  • El Mustapha Mouaddib
    • 1
  1. 1.Centre de Robotique, Electrotechnique et Automatique, Université de Picardie Jules VerneAmiensFrance

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