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Image Segmentation with Context

  • Anders P. Eriksson
  • Carl Olsson
  • Fredrik Kahl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

We present a technique for simultaneous segmentation and classification of image partitions using combinatorial optimization techniques. By combining existing image segmentation approaches with simple learning techniques we show how prior knowledge can be incorporated into the visual grouping process through the formulation of a quadratic binary optimization problem. We further show how such to efficiently solve such problems through relaxation techniques and trust region methods. This has resulted in an method that partitions images into a number of disjoint regions based on previously learned example segmentations. Preliminary experimental results are also presented in support of our suggested approach.

Keywords

Image Segmentation Gaussian Mixture Model Trust Region Relaxation Technique Trust Region Method 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Anders P. Eriksson
    • 1
  • Carl Olsson
    • 1
  • Fredrik Kahl
    • 1
  1. 1.Centre for Mathematical Sciences, Lund University, LundSweden

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