research-article

Figure-Ground Discrimination: A Combinatorial Optimization Approach

Authors:

R. HoraudAuthors Info & Claims

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 15, Issue 9

Pages 899 - 914

https://doi.org/10.1109/34.232076

Published: 01 September 1993 Publication History

Abstract

The figure-ground discrimination problem is considered from a combinatorial optimization perspective. A mathematical model encoding the figure-ground discrimination problem that makes explicit a definition of shape based on cocircularity, smoothness, proximity, and contrast is presented. This model consists of building a cost function on the basis of image element interactions. This cost function fits the constraints of an interacting spin system that, in turn, is a well suited physical model that solves hard combinatorial optimization problems. Two combinatorial optimization methods for solving the figure-ground problem, namely mean field annealing, which combines mean field approximation theory and annealing, and microcanonical annealing, are discussed. Mean field annealing may be viewed as a deterministic approximation of stochastic methods such as simulated annealing. The theoretical bases of these methods are described, and the computational models are derived. The efficiencies of mean field annealing, simulated annealing, and microcanonical annealing algorithms are compared. Within the framework of such a comparison, the figure-ground problem may be viewed as a benchmark.

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cover image IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 15, Issue 9

September 1993

125 pages

ISSN:0162-8828

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Copyright © Copyright © 1993 IEEE. All Rights Reserved.

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IEEE Computer Society

United States

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Published: 01 September 1993

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Bergmann RFitschen JPersch JSteidl G(2017)Iterative Multiplicative Filters for Data LabelingInternational Journal of Computer Vision10.1007/s11263-017-0995-9123:3(435-453)Online publication date: 1-Jul-2017
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Åström FPetra SSchmitzer BSchnörr C(2017)Image Labeling by AssignmentJournal of Mathematical Imaging and Vision10.1007/s10851-016-0702-458:2(211-238)Online publication date: 1-Jun-2017
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