A Multi-Layer ‘Gas of Circles’ Markov Random Field Model for the Extraction of Overlapping Near-Circular Objects

  • Jozsef Nemeth
  • Zoltan Kato
  • Ian Jermyn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6915)


We propose a multi-layer binary Markov random field (MRF) model that assigns high probability to object configurations in the image domain consisting of an unknown number of possibly touching or overlapping near-circular objects of approximately a given size. Each layer has an associated binary field that specifies a region corresponding to objects. Overlapping objects are represented by regions in different layers. Within each layer, long-range interactions favor connected components of approximately circular shape, while regions in different layers that overlap are penalized. Used as a prior coupled with a suitable data likelihood, the model can be used for object extraction from images, e.g. cells in biological images or densely-packed tree crowns in remote sensing images. We present a theoretical and experimental analysis of the model, and demonstrate its performance on various synthetic and biomedical images.


Active Contour Markov Random Field Tree Crown Image Domain Active Contour Model 
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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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jozsef Nemeth
    • 1
  • Zoltan Kato
    • 1
  • Ian Jermyn
    • 2
  1. 1.Image Processing and Computer Graphics DepartmentUniversity of SzegedSzegedHungary
  2. 2.Department of Mathematical SciencesDurham UniversityDurhamUnited Kingdom

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