DocumentCode
2463189
Title
Discrete models for energy-minimizing segmentation
Author
Ackah-Miezan, A. ; Gagalowicz, A.
Author_Institution
INRIA-Rocquencourt, Le Chesnay, France
fYear
1993
fDate
11-14 May 1993
Firstpage
200
Lastpage
207
Abstract
The image segmentation problem may be considered as the search for a way to subdivide an image domain into regions which represent the projection of visible parts of objects in a real scene. The authors analyze the problem of image segmentation in the framework of the approximation theory as defined by D. Mumford and J. Shah (1988). They show that for real images the problem of the choice of the energy functional is dictated by the model of the world, and they propose a method to optimize it based on a deterministic algorithm processed at multiple levels of resolution. Problems encountered in dealing with real scenes lead to several modifications of the algorithm and the energy functional. Images are shown on which the algorithm was tested
Keywords
approximation theory; deterministic algorithms; image segmentation; approximation theory; deterministic algorithm; discrete models; energy functional; energy-minimizing segmentation; image domain; image segmentation problem; regions; Approximation methods; Energy measurement; Image analysis; Image processing; Image reconstruction; Image segmentation; Layout; Light sources;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 1993. Proceedings., Fourth International Conference on
Conference_Location
Berlin
Print_ISBN
0-8186-3870-2
Type
conf
DOI
10.1109/ICCV.1993.378219
Filename
378219
Link To Document