Abstract
In this paper we describe a new technique for general purpose
interactive segmentation of N-dimensional images. The user marks certain
pixels as “object” or “background” to provide
hard constraints for segmentation. Additional soft constraints
incorporate both boundary and region information. Graph cuts are used to
find the globally optimal segmentation of the N-dimensional image. The
obtained solution gives the best balance of boundary and region
properties among all segmentations satisfying the constraints. The
topology of our segmentation is unrestricted and both
“object” and “background” segments may consist
of several isolated parts. Some experimental results are presented in
the context of photo/video editing and medical image segmentation. We
also demonstrate an interesting Gestalt example. A fast implementation
of our segmentation method is possible via a new max-flow
algorithm
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