More-Than-Topology-Preserving Flows for Active Contours and Polygons
Author(s)
Sundaramoorthi, Ganesh
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Abstract
Active contour and active polygon models have been
used widely for image segmentation. In some applications,
the topology of the object(s) to be detected from an image is
known a priori, despite an unknown complex geometry, and it is important that the active contour or polygon maintain the desired topology. In this work, we construct a novel geometric
flow that can be added to image based evolutions of
active contours and polygons so that the topology of the initial
contour or polygon is preserved. Indeed, the proposed
geometric flow ensures more than just correct topology; it
ensures that the active contour or polygon is, in some sense,
kept far away from a topology change. Smoothness properties
similar to curvature flow are also guaranteed by the
proposed geometric flow. The proposed topology preserving
geometric flow is the gradient flow arising from an energy
that is based on electrostatic principles. The evolution of a
single point on the contour depends on all other points of
the contour, which is different from traditional curve evolutions
in computer vision literature.
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Date
2005-10
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Text
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Proceedings