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Robust N-Dimensional Orientation Estimation using Quadrature Filters and Tensor Whitening
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9091-4724
n/a.
1994 (English)In: ICASSP: Adelaide, Australia, 1994Conference paper, Published paper (Refereed)
Abstract [en]

In this paper it is shown how estimates of local structure and orientation can be obtained using a set of spherically separable quadrature filters. The method is applicable to signals of any dimensionality the only requirement being that the filter set spans the corresponding orientation space. The estimates produced are 2:nd order tensors, the size of the tensors corresponding to the dimensionality of the input signal. A central part of the algorithm is an operation termed Tensor Whitening reminiscent of classical whitening procedures. This operation compensates exactly for any biases introduced by non-uniform filter orientation distributions and/or non-uniform filter output certainties. Examples of processing of 2D-images, 3D-volumes and 2D-image sequences are given. Sensitivity to noise and missing filter outputs are analyzed in different situations. Estimation accuracy as a function of filter orientation distributions are studied. The studies provide evidence that the algorithm is robust and preferable to other algorithms in a wide range of situations.

Place, publisher, year, edition, pages
1994.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-21663OAI: oai:DiVA.org:liu-21663DiVA: diva2:245986
Available from: 2009-10-08 Created: 2009-10-05 Last updated: 2013-08-28

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Knutsson, Hans

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf