Recovering Affine Deformations of Fuzzy Shapes

  • Attila Tanács
  • Csaba Domokos
  • Nataša Sladoje
  • Joakim Lindblad
  • Zoltan Kato
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5575)


Fuzzy sets and fuzzy techniques are attracting increasing attention nowadays in the field of image processing and analysis. It has been shown that the information preserved by using fuzzy representation based on area coverage may be successfully utilized to improve precision and accuracy of several shape descriptors; geometric moments of a shape are among them. We propose to extend an existing binary shape matching method to take advantage of fuzzy object representation. The result of a synthetic test show that fuzzy representation yields smaller registration errors in average. A segmentation method is also presented to generate fuzzy segmentations of real images. The applicability of the proposed methods is demonstrated on real X-ray images of hip replacement implants.


Segmentation Method Fuzzy Membership Registration Method Polynomial System Synthetic Image 
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 2009

Authors and Affiliations

  • Attila Tanács
    • 1
  • Csaba Domokos
    • 1
  • Nataša Sladoje
    • 2
  • Joakim Lindblad
    • 3
  • Zoltan Kato
    • 1
  1. 1.Department of Image Processing and Computer GraphicsUniversity of SzegedHungary
  2. 2.Faculty of EngineeringUniversity of Novi SadSerbia
  3. 3.Centre for Image AnalysisSwedish University of Agricultural SciencesUppsalaSweden

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