Characterising Meanders Qualitatively

  • Björn Gottfried
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4197)


In this paper, a qualitative shape representation is described for the purpose of characterising linear geographical and artificial objects. In particular, we focus on the curve progression telling us how objects spread across the landscape. For instance, sinuosities of rivers provide important information about imperilled locations in the case of flood waters. However, precise geometrical descriptions are overdetermined and frequently difficult or sometimes impossible to obtain. By contrast, we introduce a concept which allows curves to be classified on the basis of a qualitative representation that defines properties of linear objects, which derive from how segments of objects are located relative to other segments, arriving at conclusions such as how twisty a curve is. Especially, the new method can be applied if only coarse information is available and even then if objects are given incompletely.


Line Segment Granularity Level Qualitative Representation Simple Polygon Neighbourhood Relation 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Björn Gottfried
    • 1
  1. 1.Artificial Intelligence Group, TZIUniversity of BremenGermany

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