Interpreting line drawing images: A knowledge level perspective

Abstract

Image understanding systems rely heavily on a priori knowledge of their application domain, often exploiting techniques developed in the wider field of knowledge-based systems (KBSs). Despite attempts, typified by the KADS/CommonKADS projects, to develop structured knowledge engineering approaches to KBS development, those working in image understanding continue to employ unstructured 1st generation KBS methods. We analyse some existing image understanding systems, concerned with the interpretation of images of line drawings, from a knowledge engineering perspective. Attention focuses on the relationship between the structure of the systems considered and the KADS/CommonKADS models of expertise, sometimes called generic task models. Mappings are identified between each system and an appropriate task model, identifying common inference structures and use of knowledge. This is the first step in the acquisition of models of the expertise underpinning drawing interpretation. Such models would bring significant benefits to the design, maintenance and understanding of line drawing interpretation systems.