A Hierarchical Knowledge Based System for Airplane Classification

Authors:
D. I. Moldovan;C.-I. Wu
Affiliations:
Univ. of Southern California, Los Angeles;Univ. of Colorado at Denver, Denver
Venue:
IEEE Transactions on Software Engineering - Special Issue on Artificial Intelligence in Software Applications
Year:
1988

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Abstract

Airplane classification is used as an application domain to illustrate how hierarchical reasoning on large knowledge bases can be implemented. The knowledge base is organized as a two-dimensional hierarchy: one dimension corresponds to the levels of complexity often seen in computer vision, and the other dimension corresponds to the complexity of hypothesis used in the reasoning process. Reasoning proceeds top-down, from more abstract levels with fewer details toward levels with more details. Whenever possible, with the help of domain knowledge, decision is taken at a higher level, which significantly reduces processing time. A software package called RuBICS (Rule-Based Image Classification System) is described, and some examples of airplane classification are shown.