@InProceedings{	  stelldinger:2006a:tci,
  author	= {Stelldinger, Peer and K{\"o}the, Ullrich and Meine, Hans},
  title		= {Topologically Correct Image Segmentation Using Alpha
		  Shapes},
  booktitle	= {Proc. DGCI 2006},
  year		= {2006},
  editor	= {{Kuba, Attila and Ny{\'u}l, L{\'a}szl{\'o} G. and
		  Pal{\'a}gyi, K{\'a}lm{\'a}n}},
  series	= {Lecture Notes in Computer Science},
  volume	= {4245},
  pages		= {542--554},
  month		= oct,
  url		= {http://kogs-www.informatik.uni-hamburg.de/~meine/publications/alphashapesegmentation_dgci.pdf}
		  ,
  html		= {\htmladdnormallink{PDF,
		  357kb}{http://kogs-www.informatik.uni-hamburg.de/~meine/publications/alphashapesegmentation_dgci.pdf}}
		  ,
  location	= {Szeged, Hungary},
  abstract	= {\input{../BIB/stelldinger:2006A:tci}},
  abstracttext	= {Existing theories on shape digitization impose strong
		  constraints on feasible shapes and require error-free
		  measurements. We use Delaunay triangulation and
		  alpha-shapes to prove that topologically correct
		  segmentations can be obtained under much more realistic
		  conditions. Our key assumption is that sampling points
		  represent object boundaries with a certain maximum error.
		  Experiments on real and generated images demonstrate the
		  good performance and correctness of the new method.},
  isbn		= {3-540-47651-2}
}