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10.5555/645315.649167guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Image Processing Done Right

Published: 28 May 2002 Publication History

Abstract

A large part of "image processing" involves the computation of significant points, curves and areas ("features"). These can be defined as loci where absolute differential invariants of the image assume fiducial values, taking spatial scale and intensity (in a generic sense) scale into account. "Differential invariance" implies a group of "similarities" or "congruences". These "motions" define the geometrical structure of image space. Classical Euclidian invariants don't apply to images because image space is non-Euclidian. We analyze image structure from first principles and construct the fundamental group of image space motions. Image space is a Cayley-Klein geometry with one isotropic dimension. The analysis leads to a principled definition of "features" and the operators that define them.

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cover image Guide Proceedings
ECCV '02: Proceedings of the 7th European Conference on Computer Vision-Part I
May 2002
810 pages

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 28 May 2002

Author Tags

  1. image features
  2. image indexing
  3. image space
  4. image transformations
  5. scale-space
  6. texture

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