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Proceedings Paper

Ship Classification And Aimpoint Maintenance
Author(s): D. N. Kato; R. D. Holben; A. S. Politopoulos; B. H. Yin
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Paper Abstract

This paper describes a suite of target cueing algorithms which has been developed for the recognition of ship targets in the open ocean through FLIR Imagery. Imaging prepro cessing is first used to remove pattern and temporal noise. A relaxation technique is implemented to extract the target's silhouette. The superstructure profile is then obtained and classification is performed based on low-order coefficients of the discrete Fourier transform of the profile. This classification approach was found to have a 93% accuracy for short ranges (7-11 miles) and 70% accuracy for long ranges (11-20 miles) for eight target classes tested against 11398 images. Finally, a terminal homing algo rithm is described which incorporates scene tracking for maintaining track on a selected aimpoint which demonstrates superior performance over more conventional approaches.

Paper Details

Date Published: 3 May 1988
PDF: 8 pages
Proc. SPIE 0890, Infrared Systems and Components II, (3 May 1988); doi: 10.1117/12.944286
Show Author Affiliations
D. N. Kato, Ford Aerospace Corporation (United States)
R. D. Holben, Ford Aerospace Corporation (United States)
A. S. Politopoulos, Ford Aerospace Corporation (United States)
B. H. Yin, Ford Aerospace Corporation (United States)

Published in SPIE Proceedings Vol. 0890:
Infrared Systems and Components II
H.M. Charles Liaw, Editor(s)

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