A Markov Random Field Model for Extracting Near-Circular Shapes (bibtex)
by Tamas Blaskovics, Zoltan Kato, Ian Jermyn
Abstract:
We propose a binary Markov Random Field (MRF) model that assigns high probability to regions in the image domain consisting of an unknown number of circles of a given radius. We construct the model by discretizing the 'gas of circles' phase field model in a principled way, thereby creating an 'equivalent' MRF. The behaviour of the resulting MRF model is analyzed, and the performance of the new model is demonstrated on various synthetic images as well as on the problem of tree crown detection in aerial images.
Reference:
Tamas Blaskovics, Zoltan Kato, Ian Jermyn, A Markov Random Field Model for Extracting Near-Circular Shapes, In Proceedings of International Conference on Image Processing, Cairo, Egypt, pp. 1073-1076, 2009, IEEE.
Bibtex Entry:
@string{icip="Proceedings of International Conference on Image Processing"}
@InProceedings{Blaskovics-etal2009a,
  author =	 {Tamas Blaskovics and Kato, Zoltan and Ian Jermyn},
  title =	 {A {M}arkov Random Field Model for Extracting
                  Near-Circular Shapes},
  booktitle =	 icip,
  pages =	 {1073--1076},
  year =	 2009,
  address =	 {Cairo, Egypt},
  month =	 nov,
  organization = {IEEE},
  publisher =	 {IEEE},
  abstract =	 {We propose a binary Markov Random Field (MRF) model
                  that assigns high probability to regions in the
                  image domain consisting of an unknown number of
                  circles of a given radius. We construct the model by
                  discretizing the 'gas of circles' phase
                  field model in a principled way, thereby creating an
                  'equivalent' MRF. The behaviour of the
                  resulting MRF model is analyzed, and the performance
                  of the new model is demonstrated on various
                  synthetic images as well as on the problem of tree
                  crown detection in aerial images.},
  pdf =		 {papers/icip2009.pdf}
}
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