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Characterization of Similar Areas of Two 2D Point Clouds

  • Sébastien Mavromatis
  • Christophe Palmann
  • Jean Sequeira
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7432)

Abstract

We here present a new approach to characterize similar areas of two 2D point clouds, which is a major issue in Pattern Recognition and Image Analysis.

To do so, we define a similarity measure that takes into account several criteria such as invariance by rotation, outlier elimination, and one-dimensional structure enhancement. We use this similarity measure to associate locations from one cloud to the other, to use this result in the frame of a registration process between these two point clouds.

Our main contributions are the integration of various one-dimensional structure representations into a unified formalism, and the design of a robust estimator to evaluate the common information related to these structures.

Finally, we show how to use this approach to register images of different modalities.

Keywords

Remote Sensing Point Cloud Multispectral Image Robust Estimator Similar Area 
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 2012

Authors and Affiliations

  • Sébastien Mavromatis
    • 1
  • Christophe Palmann
    • 1
  • Jean Sequeira
    • 1
  1. 1.Projet SimGraph - LSIS UMR CNRS 7296Aix-Marseille Université Polytech Marseille case 925Marseille Cedex 9France

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