Computing a Family of Skeletons of Volumetric Models for Shape Description

  • Tao Ju
  • Matthew L. Baker
  • Wah Chiu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4077)


Skeletons are important shape descriptors in object representation and recognition. Typically, skeletons of volumetric models are computed via an iterative thinning process. However, traditional thinning methods often generate skeletons with complex structures that are unsuitable for shape description, and appropriate pruning methods are lacking. In this paper, we present a new method for computing skeletons on volumes by alternating thinning and a novel skeleton pruning routine. Our method creates a family of skeletons parameterized by two user-specified numbers that determine respectively the size of curve and surface features on the skeleton. As demonstrated on both real-world models and medical images, our method generates skeletons with simple and meaningful structures that are particularly suitable for describing cylindrical and plate-like shapes.


Medial Axis Object Point Image Denoising Pruning Method Object Versus 
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

  • Tao Ju
    • 1
  • Matthew L. Baker
    • 2
  • Wah Chiu
    • 2
  1. 1.Washington UniversitySt. Louis
  2. 2.Baylor College of MedicineHouston

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