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Experiments on Robust Image Registration Using a Markov-Gibbs Appearance Model

  • Ayman El-Baz
  • Aly Farag
  • Georgy Gimel’farb
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4109)

Abstract

A new approach to align an image of a textured object with a given prototype under its monotone photometric and affine geometric transformations is experimentally compared to more conventional registration algorithms. The approach is based on measuring similarity between the image and prototype by Gibbs energy of characteristic pairwise co-occurrences of the equalized image signals. After an initial alignment, the affine transformation maximizing the energy is found by gradient search. Experiments confirm that our approach results in more robust registration than the search for the maximal mutual information or similarity of scale-invariant local features.

Keywords

Image Registration Scale Invariant Feature Transform Appearance Model Gradient Search Texture Object 
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

  • Ayman El-Baz
    • 1
  • Aly Farag
    • 1
  • Georgy Gimel’farb
    • 2
  1. 1.Computer Vision and Image Processing LaboratoryUniversity of LouisvilleLouisville
  2. 2.Department of Computer ScienceUniversity of AucklandAucklandNew Zealand

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