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Semantic description of aerial images using stochastic labeling
1MEMBER, IEEE, Image Processing Institute, University of Southern California, Los Angeles, CA 90007; Institut National de Recherche en Informatique et en Automatique, Le Chesnay, Fr.
Abstract:
This paper discusses the application of stochastic labeling to a general symbolic image description problem. A method used to compute initial likelihoods and compatibilities is described. It was derived from an earlier symbolic matching procedure, but was modified to provide the data needed for application of the labeling method. This labeling procedure differs from simpler ones, in that it minimizes a global criterion at each iteration. This technique is compared to other matching methods, and results on two scenes are presented.
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