Target Recognition For Missile Guidance Using Adaptive Learning Networks

Joseph N. Craig; Michael F. Whalen; Francis J. Cook

doi:10.1117/12.959160

23 December 1980 Target Recognition For Missile Guidance Using Adaptive Learning Networks

Joseph N. Craig, Michael F. Whalen, Francis J. Cook

Author Affiliations +

Proceedings Volume 0238, Image Processing for Missile Guidance; (1980) https://doi.org/10.1117/12.959160
Event: 24th Annual Technical Symposium, 1980, San Diego, United States

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.

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Joseph N. Craig, Michael F. Whalen, and Francis J. Cook "Target Recognition For Missile Guidance Using Adaptive Learning Networks", Proc. SPIE 0238, Image Processing for Missile Guidance, (23 December 1980); https://doi.org/10.1117/12.959160

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