Image segmentation by nested cuts
Veksler, O.
NEC Res. Inst., Princeton, NJ;
This paper appears in: Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on
Publication Date: 2000
Volume: 1,
On page(s): 339-344 vol.1
Meeting Date: 06/13/2000 - 06/15/2000
Location: Hilton Head Island, SC, USA
ISBN: 0-7695-0662-3
References Cited: 10
INSPEC Accession Number: 6651653
Digital Object Identifier: 10.1109/CVPR.2000.855838
Current Version Published: 2002-08-06
Abstract
We present a new image segmentation algorithm based on graph cuts.
Our main tool is separation of each pixel p from a special point outside
the image by a cut of a minimum cost. Such a cut creates a group of
pixels Cp around each pixel. We show that these groups
Cp are either disjoint or nested in each other and so they
give a natural segmentation of the image. In addition this property
allows an efficient implementation of the algorithms because for most
pixels p the computation of Cp is not performed on the whole
graph. We inspect all Cp and discard those which are not
interesting, for example if they are too small. This procedure
automatically groups small components together or merges them into
nearby large clusters. Effectively, our segmentation is performed by
extracting significant non-intersecting closed contours. We present
interesting segmentation results on real and artificial images
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