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Proceedings Paper

Neural Networks For Adaptive Shape Tracking
Author(s): Alastair McAulay; Ivan Kadar
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Paper Abstract

A practical approach to tracking aircraft with similar looking silhouettes while maintaining identification is proposed and simulated. Preprocessing is performed using moment invariants that are shown to be almost constant for images in which the object is translated in position, rotated, or changed in scale. These moment invariants are used to train a neural network to identify the aircraft for different aspect angles. Consequently, tracking of a specific aircraft is achieved no matter what the aspect angle, the position, rotation, or scale.

Paper Details

Date Published: 5 September 1989
PDF: 9 pages
Proc. SPIE 1099, Advances in Image Compression and Automatic Target Recognition, (5 September 1989); doi: 10.1117/12.960455
Show Author Affiliations
Alastair McAulay, Wright State University (United States)
Ivan Kadar, Grumman Corporation (United States)


Published in SPIE Proceedings Vol. 1099:
Advances in Image Compression and Automatic Target Recognition
Andrew G. Tescher, Editor(s)

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