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Image interpretation using Bayesian networks

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2 Author(s)
V. P. Kumar ; Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA ; U. B. Desai

The problem of image interpretation is one of inference with the help of domain knowledge. In this paper, we formulate the problem as the maximum a posteriori (MAP) estimate of a properly defined probability distribution function (PDF). We show that a Bayesian network can be used to represent this PDF as well as the domain knowledge needed for interpretation. The Bayesian network may be relaxed to obtain the set of optimum interpretations

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:18 ,  Issue: 1 )