Knowledge Representation

  • Gerhard Sagerer
  • Heinrich Niemann
Part of the Advances in Computer Vision and Machine Intelligence book series (ACVM)


Already in the introduction — see section 1.2 — a first clarification of the term knowledge in the context of image analysis was started. We distinguished three different aspects and five general levels of knowledge for the discussed context. Based on these distinctions and the proposed homogenous system architecture — see section 1.3 — this chapter will address the problem of knowledge representation. As a first-order approximation this requires the storage of the entities of the aspects and levels as mentioned above. Especially the representation of constraints and associations between objects and events in the real world is necessary. This is also a reminiscent of Postulate 3 in section 1.1 where the existence of structure in a complex pattern was required.


Knowledge Representation Inference Rule Semantic Network Inference Process Segmentation Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Gerhard Sagerer
    • 1
  • Heinrich Niemann
    • 2
  1. 1.Universität BielefeldBielefeldGermany
  2. 2.Universität Erlangen-NürnbergErlangenGermany

Personalised recommendations