Image interpretation using Bayesian networks

被引：19
|
作者：
Kumar, VP [1 ]
Desai, UB [1 ]
机构：
[1] INDIAN INST TECHNOL,DEPT ELECT ENGN,BOMBAY 400076,MAHARASHTRA,INDIA
来源：
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1996年 / 18卷 / 01期
关键词：
artificial intelligence; Bayesian networks; expert systems; object recognition; image interpretation; decision making; inference systems; Markov random fields;
D O I：
10.1109/34.476423
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The problem of image interpretation is one of inference with the help of domain knowledge. In this correspondence, we formulate the problem as the maximum a posteriori (MAP) estimate of a properly defined probability distribution function. We show that a Bayesian network can be used to represent this p.d.f. as well as the domain knowledge needed for interpretation. The Bayesian network may be relaxed to obtain the set of optimum interpretations.
引用
收藏
页码：74 / 77
页数：4
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