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Image loci are ridges in geometric spaces

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Scale-Space Theory in Computer Vision (Scale-Space 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1252))

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Abstract

In this paper, we show that most interesting features in an image, such as boundaries and skeletons, are height ridges in an extended Euclidean space, the extension parameters being directions and aperture. We define the notion of a height ridge and show how height ridges have been used by other authors. We also provide a catalog of useful variations of the basic definition. We then show the generic behavior of the maximal convexity form of ridge and its generic transitions in one parameter families. Finally, we discuss connectors, an extension to such ridges.

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Author information

Authors and Affiliations

  1. Medical Image Display and Analysis Group, University of North Carolina, 27599, Chapel Hill, NC

    Jacob D. Furst, Robert S. Keller, Jason E. Miller & Stephen M. Pizer

Authors
  1. Jacob D. Furst
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  2. Robert S. Keller
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  3. Jason E. Miller
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  4. Stephen M. Pizer
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Editor information

Bart ter Haar Romeny Luc Florack Jan Koenderink Max Viergever

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© 1997 Springer-Verlag Berlin Heidelberg

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Furst, J.D., Keller, R.S., Miller, J.E., Pizer, S.M. (1997). Image loci are ridges in geometric spaces. In: ter Haar Romeny, B., Florack, L., Koenderink, J., Viergever, M. (eds) Scale-Space Theory in Computer Vision. Scale-Space 1997. Lecture Notes in Computer Science, vol 1252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63167-4_49

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  • DOI: https://doi.org/10.1007/3-540-63167-4_49

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63167-5

  • Online ISBN: 978-3-540-69196-9

  • eBook Packages: Springer Book Archive

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