Shape modeling with front propagation: a level set approach

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 overcom...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 1995-02, Vol.17 (2), p.158-175
Hauptverfasser: Malladi, R., Sethian, J.A., Vemuri, B.C.
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container_title IEEE transactions on pattern analysis and machine intelligence
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creator Malladi, R.
Sethian, J.A.
Vemuri, B.C.
description 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.< >
doi_str_mv 10.1109/34.368173
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identifier ISSN: 0162-8828
ispartof IEEE transactions on pattern analysis and machine intelligence, 1995-02, Vol.17 (2), p.158-175
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language eng
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source IEEE Electronic Library (IEL)
subjects Applied sciences
Artificial intelligence
Biomedical imaging
Computer graphics
Computer science
control theory
systems
Computer vision
Difference equations
Exact sciences and technology
Finite difference methods
Level set
Narrowband
Pattern recognition. Digital image processing. Computational geometry
Shape
Simulation
Software
Solid modeling
Topology
title Shape modeling with front propagation: a level set approach
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