Shape modeling with front propagation: a level set approach
Malladi, R.
Sethian, J.A.
Vemuri, B.C.
Lawrence Berkeley Lab., California Univ., Berkeley, CA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Feb 1995
Volume: 17,
Issue: 2
On page(s): 158-175
ISSN: 0162-8828
References Cited: 40
CODEN: ITPIDJ
INSPEC Accession Number: 4887738
Digital Object Identifier: 10.1109/34.368173
Current Version Published: 2002-08-06
Abstract
Shape modeling is an important constituent of computer vision as
well as computer graphics research. Shape models aid the tasks of object
representation and recognition. This paper presents a new approach to
shape modeling which retains some of the attractive features of existing
methods and overcomes some of their limitations. The authors' techniques
can be applied to model arbitrarily complex shapes, which include shapes
with significant protrusions, and to situations where no a priori
assumption about the object's topology is made. A single instance of the
authors' model, when presented with an image having more than one object
of interest, has the ability to split freely to represent each object.
This method is based on the ideas developed by Osher and Sethian (1988)
to model propagating solid/liquid interfaces with curvature-dependent
speeds. The interface (front) is a closed, nonintersecting, hypersurface
flowing along its gradient field with constant speed or a speed that
depends on the curvature. It is moved by solving a
“Hamilton-Jacobi” type equation written for a function in
which the interface is a particular level set. A speed term synthesized
from the image is used to stop the interface in the vicinity of object
boundaries. The resulting equation of motion is solved by employing
entropy-satisfying upwind finite difference schemes. The authors present
a variety of ways of computing the evolving front, including narrow
bands, reinitializations, and different stopping criteria. The efficacy
of the scheme is demonstrated with numerical experiments on some
synthesized images and some low contrast medical images
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