Voronoi Pyramids controlled by Hopfield Neural Networks (bibtex)
by Etienne Bertin, Horst Bischof
Abstract:
We present an algorithm for image segmentation with irregular pyramids. Instead of starting with the original pixel grid, we first apply some adaptive Voronoi tesselation to the image. This provides the advantage that the number of cells in the bottom level of the pyramid is already reduced as compared to the number of pixels of the original image. Furthermore the Voronoi diagram is a powerful tool for shape description and image compression. For the construction of the irregular pyramid we present a Hopfield neural network which controls the decimation process. In this paper we extend our previous results by proving a more general theorem. The contributions of this paper are the initialisation of the pyramid by a Delaunay graph and the extension of the results for Hopfield neural networks for decimation. The validity of our approach is demonstrated by several examples.
Reference:
Voronoi Pyramids controlled by Hopfield Neural Networks (Etienne Bertin, Horst Bischof), Technical report, PRIP, TU Wien, 1993.
Bibtex Entry:
@TechReport{TR024,
  author =	 "Etienne Bertin and Horst Bischof",
  institution =	 "PRIP, TU Wien",
  number =	 "PRIP-TR-024",
  title =	 "Voronoi {P}yramids controlled by {H}opfield {N}eural
                  {N}etworks",
  year =	 "1993",
  url =		 "ftp://ftp.prip.tuwien.ac.at/pub/publications/trs/tr24.ps.gz",
  abstract =	 "We present an algorithm for image segmentation with
                  irregular pyramids. Instead of starting with the
                  original pixel grid, we first apply some adaptive
                  Voronoi tesselation to the image. This provides the
                  advantage that the number of cells in the bottom
                  level of the pyramid is already reduced as compared
                  to the number of pixels of the original
                  image. Furthermore the Voronoi diagram is a powerful
                  tool for shape description and image
                  compression. For the construction of the irregular
                  pyramid we present a Hopfield neural network which
                  controls the decimation process. In this paper we
                  extend our previous results by proving a more
                  general theorem. The contributions of this paper are
                  the initialisation of the pyramid by a Delaunay
                  graph and the extension of the results for Hopfield
                  neural networks for decimation. The validity of our
                  approach is demonstrated by several examples.",
}
Powered by bibtexbrowser