Active contours without edges
Chan, T.F.; Vese, L.A.
Image Processing, IEEE Transactions on
Volume 10, Issue 2, Feb 2001 Page(s):266 - 277
Digital Object Identifier 10.1109/83.902291
Summary:We propose a new model for active contours to detect objects in a
given image, based on techniques of curve evolution, Mumford-Shah (1989)
functional for segmentation and level sets. Our model can detect objects
whose boundaries are not necessarily defined by the gradient. We
minimize an energy which can be seen as a particular case of the minimal
partition problem. In the level set formulation, the problem becomes a
“mean-curvature flow”-like evolving the active contour,
which will stop on the desired boundary. However, the stopping term does
not depend on the gradient of the image, as in the classical active
contour models, but is instead related to a particular segmentation of
the image. We give a numerical algorithm using finite differences.
Finally, we present various experimental results and in particular some
examples for which the classical snakes methods based on the gradient
are not applicable. Also, the initial curve can be anywhere in the
image, and interior contours are automatically detected
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