Analysis of Superimposed Oriented Patterns

  title={Analysis of Superimposed Oriented Patterns},
  author={Til Aach and Cicero Mota and Ingo Stuke and Matthias M{\"u}hlich and Erhardt Barth},
  journal={IEEE Transactions on Image Processing},
Estimation of local orientation in images may be posed as the problem of finding the minimum gray-level variance axis in a local neighborhood. In bivariate images, the solution is given by the eigenvector corresponding to the smaller eigenvalue of a 2times2 tensor. For an ideal single orientation, the tensor is rank-deficient, i.e., the smaller eigenvalue vanishes. A large minimal eigenvalue signals the presence of more than one local orientation, what may be caused by non-opaque additive or… CONTINUE READING


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