@string{icvgip="Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing"}
@string{lncs="Lecture Notes in Computer Science"}
@string{springer="Springer"}
@InProceedings{Horvath-etal2006a,
  author =	 {Peter Horvath and Ian Jermyn and Zoltan Kato and
                  Josiane Zerubia},
  title =	 {An improved `gas of circles' higher-order active
                  contour model and its application to tree crown
                  extraction},
  booktitle =	 icvgip,
  pages =	 {152--161},
  year =	 2006,
  editor =	 {Prem Kalra and Shmuel Peleg},
  volume =	 4338,
  series =	 lncs,
  address =	 {Madurai, India},
  month =	 dec,
  publisher =	 springer,
  pdf =		 {papers/icvgip2006.pdf},
  abstract =	 {A central task in image processing is to find the
                  region in the image corresponding to an entity. In a
                  number of problems, the region takes the form of a
                  collection of circles, e.g. tree crowns in remote
                  sensing imagery; cells in biological and medical
                  imagery. In [1], a model of such regions, the 'gas
                  of circles' model, was developed based on
                  higher-order active contours, a recently developed
                  framework for the inclusion of prior knowledge in
                  active contour energies. However, the model suffers
                  from a defect. In [1], the model parameters were
                  adjusted so that the circles were local energy
                  minima. Gradient descent can become stuck in these
                  minima, producing phantom circles even with no
                  supporting data. We solve this problem by
                  calculating, via a Taylor expansion of the energy,
                  parameter values that make circles into energy
                  inflection points rather than minima. As a bonus,
                  the constraint halves the number of model
                  parameters, and severely constrains one of the two
                  that remain, a major advantage for an energy-based
                  model. We use the model for tree crown extraction
                  from aerial images. Experiments show that despite
                  the lack of parametric freedom, the new model
                  performs better than the old, and much better than a
                  classical active contour.}
}