Image Interpretation Using Bayesian Networks

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.

[1]  Richard E. Neapolitan,et al.  Probabilistic reasoning in expert systems - theory and algorithms , 2012 .

[2]  Jun Zhang,et al.  A Markov Random Field Model-Based Approach to Image Interpretation , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Il Y. Kim,et al.  Efficient image labeling based on markov random field and error backpropagation network , 1993, Pattern Recognit..

[4]  J. McDermott,et al.  Rule-Based Interpretation of Aerial Imagery , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Y. Ohta.  Knowledge-based interpretation of outdoor natural color scenes , 1998 .

[6]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[7]  James W. Modestino,et al.  A Markov Random Field Model-Based Approach To Image Interpretation , 1989, Other Conferences.

[8]  Judea Pearl,et al.  Causal networks: semantics and expressiveness , 2013, UAI.

[9]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[10]  Richard E. Neapolitan,et al.  Probabilistic reasoning in expert systems - theory and algorithms , 2012 .

[11]  Judea Pearl,et al.  Evidential Reasoning Using Stochastic Simulation of Causal Models , 1987, Artif. Intell..

[12]  Donald Geman,et al.  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[13]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.