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Proceedings Paper

Target Recognition For Missile Guidance Using Adaptive Learning Networks
Author(s): Joseph N. Craig; Michael F. Whalen; Francis J. Cook
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Paper Abstract

The Adaptive Learning Network Synthesis methodology has been used to implement an image classification algorithm for infrared images. Using features extracted from transforms of the original image, the algorithm achieves range and aspect angle independent separation of images that contain a specific target (a tank) from images that do not contain the target. A ROC analysis of the algorithm, using 385 sample images, shows >95% detection rate, <5% false alarm rate, and a small (<1%) false dismissal rate.

Paper Details

Date Published: 23 December 1980
PDF: 7 pages
Proc. SPIE 0238, Image Processing for Missile Guidance, (23 December 1980); doi: 10.1117/12.959160
Show Author Affiliations
Joseph N. Craig, Westgate Research Park (United States)
Michael F. Whalen, Westgate Research Park (United States)
Francis J. Cook, Westgate Research Park (United States)

Published in SPIE Proceedings Vol. 0238:
Image Processing for Missile Guidance
Thomas F. Wiener, Editor(s)

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