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Proceedings Paper

A Knowledge-Based Approach To Ship Identification
Author(s): R. W. McLaren; H .-Y . Lin
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Paper Abstract

A knowledge-based ("expert") classifier was designed for classifying ship silhouettes generated from forward-looking infrared (FLIR) imagery. A knowledge-base is constructed based on interviews with a U.S. Navy officer along with confirming evidence from Jayne's Fighting Ships. This knowledge provides the means to set-up a ruled-based sequential decision tree or net. The conditions of the production rules deal with silhouette "humps" and their properties such as the number, spacing, relative placement on deck line, and the like. This classifier was applied to a sample consisting of about 500 sample silhouettes distributed about uniformly over eight classes of ship targets. Results were equal or better than results using a more "conventional" classifier.

Paper Details

Date Published: 26 March 1986
PDF: 11 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964138
Show Author Affiliations
R. W. McLaren, University of Missouri-Columbia (United States)
H .-Y . Lin, University of Missouri-Columbia (United States)

Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)

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