Discrete Topological Transformations for Image Processing

  • Michel Couprie
  • Gilles Bertrand
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 2)


Topology-based image processing operators usually aim at transforming an image while preserving its topological characteristics. This chapter reviews some approaches which lead to efficient and exact algorithms for topological transformations in 2D, 3D and grayscale images. Some transformations that modify topology in a controlled manner are also described. Finally, based on the framework of critical kernels, we show how to design a topologically sound parallel thinning algorithm guided by a priority function.


Topological Characteristic Grayscale Image Medial Axis Simple Point Cubical Complex 
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.



This work has been partially supported by the “ANR BLAN07-2_184378 MicroFiss” project and the “ANR-2010-BLAN-0205 Kidico” project.


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© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Laboratoire d’Informatique Gaspard-Monge, Équipe A3SIUniversité Paris-Est, ESIEE ParisMarne-la-ValléeFrance

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