Extraction of Haar Integral Features on Omnidirectional Images: Application to Local and Global Localization

  • Ouiddad Labbani-Igbida
  • Cyril Charron
  • El Mustapha Mouaddib
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


In this paper, we present a new 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. We suggest an averaging technique based on Haar integral invariance. It takes into account the movements the robot can do in a room and the omni image transformations thus produced.

The variability of the built signatures is adjusted (total or partial Haar invariance) according to defined subsets of the group transformation. The experimental results prove to get significantly interesting results for place recognition and robot localization with variable accuracy: From global rough localization to local precise one.


Mobile Robot Image Retrieval Scale Invariant Feature Transform Robot Localization Image Retrieval System 
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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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

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

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