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Topological classification in digital space

  • G. Malandain
  • G. Bertrand
  • N. Ayache
5. Segmentation: Multi-Scale, Surfaces And Topology
Part of the Lecture Notes in Computer Science book series (LNCS, volume 511)

Abstract

We propose in this paper a new approach to segment a discrete 3D object into a structure of characteristic topological primitives with attached qualitative features. This structure can be seen itself as a qualitative description of the object, because
  1. it is intrinsic to the 3D object, which means it is stable to rigid transformations (rotations and translations).

     
  2. it is locally defined, and therefore stable to partial occlusions and local modifications of the object structure.

     
  3. it is robust to noise and small deformations, as confirmed by our experimental results.

     

Our approach concentrates on topological properties of discrete surfaces. These surfaces may correspond to the external surface of the objects extracted by a 3D edge detector, or to the skeleton surface obtained by a new thinning algorithm. Our labeling algorithm is based on very local computations, allowing massively parallel computations and real time computations.

We present a realistic experiment to characterize and locate spatially a complex 3D medical object using the proposed segmentation of its skeleton.

Keywords

Digital topology segmentation simple surfaces image analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • G. Malandain
    • 1
  • G. Bertrand
    • 2
  • N. Ayache
    • 1
  1. 1.InriaLe Chesnay CédexFrance
  2. 2.Esiee, Labo IAAI - Cité DescartesNoisy-le-Grand CédexFrance

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