Visual Form pp 333-344 | Cite as

Entropy Scale-Space

  • Benjamin B. Kimia
  • Allen Tannenbaum
  • Steven W. Zucker


We introduce a novel notion of scale for signals which we illustrate for shape. It is based on the notion of entropy and a view of shocks as “black holes of information”. We propose that to properly place features in a hierarchy, we need both linear, global, and instantaneously propagated smoothing (e.g. Gaussian smoothing), as well as non-linear, local smoothing (e.g., certain morphological operators) that propagate information with finite speed. Both of these types of processes are brought together in the entropy scale space. The scheme is illustrated for shape, is intuitive and robust, and applicable in other areas of vision.5


Black Hole Rarefaction Wave Scale Space Jump Condition Morphological Operation 
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 Science+Business Media New York 1992

Authors and Affiliations

  • Benjamin B. Kimia
    • 1
  • Allen Tannenbaum
    • 1
    • 2
    • 3
  • Steven W. Zucker
    • 1
    • 4
    • 5
  1. 1.Laboratory for Engineering Man-Machine SystemsBrown UniversityProvidenceUSA
  2. 2.Dept. of Elect. Eng.University of MinnesotaMinneapolisUSA
  3. 3.Department of Electrical EngineeringTechnionCity-HaifaIsrael
  4. 4.Canadian Institute for Advanced ResearchCanada
  5. 5.McGill Research Center For Intelligent MachinesCanada

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