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Multiresolutional Cluster Segmentation Using Spatial Context

  • Jan J. Gerbrands
  • Eric Backer
  • Xiang S. Cheng
Conference paper
Part of the NATO ASI Series book series (volume 30)

Abstract

A multiresolutional cluster/relaxation image segmentation algorithm is described. A preliminary split-merge procedure generates variable-sized quadtree-blocks. These multiresolutional units are used in the subsequent clustering. A probabilistic relaxation procedure conducts the final labeling. A large reduction in data processing is attained by processing blocks rather than pixels, while still yielding good segmentation results.

Keywords

Active Block Spatial Context Final Segmentation Current Cluster Image Segmentation Algorithm 
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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • Jan J. Gerbrands
    • 1
  • Eric Backer
    • 1
  • Xiang S. Cheng
    • 1
  1. 1.Department of Electrical EngineeringDelft University of TechnologyDelftThe Netherlands

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