A Higher-Order Active Contour Model for Tree Detection (bibtex)
by Peter Horvath, Ian Jermyn, Zoltan Kato, Josiane Zerubia
Abstract:
We present a model of a 'gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short range repulsive interactions, and apply it to the extraction of tree crowns from aerial images. The method uses the recently introduced 'higher order active contours' (HOACs), which incorporate long-range interactions between contour points, and thereby include prior geometric information without using a template shape. This makes them ideal when looking for multiple instances of an entity in an image. We study an existing HOAC model for networks, and show via a stability calculation that circles stable to perturbations are possible for constrained parameter sets. Combining this prior energy with a data term, we show results on aerial imagery that demonstrate the effectiveness of the method and the need for prior geometric knowledge. The model has many other potential applications.
Reference:
Peter Horvath, Ian Jermyn, Zoltan Kato, Josiane Zerubia, A Higher-Order Active Contour Model for Tree Detection, In Proceedings of International Conference on Pattern Recognition, volume 2, Hong Kong, China, pp. 130-133, 2006, IEEE.
Bibtex Entry:
@string{icpr="Proceedings of International Conference on Pattern Recognition"}
@InProceedings{Horvath-etal2006,
  author =	 {Peter Horvath and Ian Jermyn and Zoltan Kato and
                  Josiane Zerubia},
  title =	 {A Higher-Order Active Contour Model for Tree
                  Detection},
  booktitle =	 icpr,
  pages =	 {130--133},
  year =	 2006,
  volume =	 2,
  address =	 {Hong Kong, China},
  month =	 aug,
  organization = {IAPR},
  publisher =	 {IEEE},
  pdf =		 {papers/icpr2006.pdf},
  abstract =	 {We present a model of a 'gas of circles', the
                  ensemble of regions in the image domain consisting
                  of an unknown number of circles with approximately
                  fixed radius and short range repulsive interactions,
                  and apply it to the extraction of tree crowns from
                  aerial images. The method uses the recently
                  introduced 'higher order active contours' (HOACs),
                  which incorporate long-range interactions between
                  contour points, and thereby include prior geometric
                  information without using a template shape. This
                  makes them ideal when looking for multiple instances
                  of an entity in an image. We study an existing HOAC
                  model for networks, and show via a stability
                  calculation that circles stable to perturbations
                  are possible for constrained parameter
                  sets. Combining this prior energy with a data term,
                  we show results on aerial imagery that demonstrate
                  the effectiveness of the method and the need for
                  prior geometric knowledge. The model has many other
                  potential applications. }
}
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