Neumann - 9 
information about the roles which some object may possibly play. If an object 
participates in many part-of relationships, i.e. if the role is 1-to-many, there 
are many aggregate candidates and the inference power may be small just 
as in situations where partial evidence is inconclusive. But if the role singles 
out only one aggregate, this information may speed up further processing 
considerably. 
Aggregate consistent with partial evidence 
The usefulness of hypotheses-generating inference services can be further 
improved by providing a ranking between hypotheses by means of a 
measure of likelihood. Carried out with all consequences, this would be 
equivalent to providing a probabilistic framework for classification. How this 
can be done in a manner consistent with a terminological system, is a topic 
of ongoing research [Jaeger 94]. 
As a less ambitious step into this direction we suggest to exploit A-box 
statistics. The A-box of a terminological system contains assertions about 
individual objects, in this case about the objects encountered in concrete 
image interpretation tasks. In the absence of other sources of statistical 
information, A-box statistics provide a valid basis for generating expectations 
about the contents of new images. In particular, given partial evidence for an 
unknown object, a likelihood ranking of candidate hypotheses can be 
provided based on past experience. 
Note that hypotheses ranking is nothing out of the ordinary for any odd 
image interpretation system. By suggesting this service for image 
interpretation in a terminological framework, we try to provide minimal 
services which such a framework must offer to be competitive. 
4. Conclusions 
In this contribution we have taken a close look at terminological systems and 
their use for image interpretation. Illustrated by an extended example taken 
from [Lange and Schroder 94] we have shown that fairly complex changes 
in aerial images can be precisely defined and automatically recognised 
using the object classifier of the terminological system. Thus, in principle, the 
construction of image interpretation systems can be greatly facilitated by 
employing standardised knowledge representation and reasoning services