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Adaptive Robust Structure Tensors for Orientation Estimation and Image Segmentation

  • Sumit K. Nath
  • Kannappan Palaniappan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3804)

Abstract

Recently, Van Den Boomgaard and Van De Weijer have presented an algorithm for texture analysis using robust tensor-based estimation of orientation. Structure tensors are a useful tool for reliably estimating oriented structures within a neighborhood and in the presence of noise. In this paper, we extend their work by using the Geman-McClure robust error function and, developing a novel iterative scheme that adaptively and simultaneously, changes the size, orientation and weighting of the neighborhood used to estimate the local structure tensor. The iterative neighborhood adaptation is initialized using the total least-squares solution for the gradient using a relatively large isotropic neighborhood. Combining our novel region adaptation algorithm, with a robust tensor formulation leads to better localization of low-level edge and junction image structures in the presence of noise. Preliminary results, using synthetic and biological images are presented.

Keywords

Pollen Tube Structure Tensor Orientation Estimation Biological Image Ideal Edge 
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 2005

Authors and Affiliations

  • Sumit K. Nath
    • 1
  • Kannappan Palaniappan
    • 1
  1. 1.MCVL, Department of Computer ScienceUniversity of Missouri-ColumbiaColumbiaUSA

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