Knowledge-based image understanding systems: A survey

被引:100
|
作者
Crevier, D
Lepage, R
机构
[1] Université du Québec, Ecl. de Technol. Supérieure, Department of Electrical Engineering, Montreal, Que. H2T 268, 4750, avenue Henri-Julien
关键词
D O I
10.1006/cviu.1996.0520
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The development of software that would be to image understanding systems what expert system shells are to expert systems has been the subject of considerable enquiry over the last ten years: this paper reviews pertinent publications and tries to present a coherent view of the field. After a survey of the advantages of explicit knowledge representation in image understanding, we tackle the subject under two main headings. We first expose the nature of the knowledge that the various authors have represented for image understanding. To this effect, we have elaborated a knowledge taxonomy consisting of seven modules, ranging in specificity from task domain knowledge to generic knowledge about the use of software systems. We then examine how researchers have represented these various kinds of knowledge. Most of the representations known to artificial intelligence were pressed into service, and a discussion of their relative merits is presented. (C) 1997 Academic Press.
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页码:161 / 185
页数:25
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