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Proceedings Paper

Automatic target recognition processor using an optical wavelet preprocessor and an electronic neural classifier
Author(s): Youngchul Park; Tien-Hsin Chao
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Paper Abstract

A comprehensive automatic target recognition (ATR) system using a wavelet transform based target detection preprocessor and a neural network classifier is described. A compact, high-speed optical wavelet processor with full gray scale filter capability, recently developed at JPL has been used for real-time target detection preprocessing. An innovative feature extraction algorithm using the Hermite Moments has been developed and used for neural net classification. The extracted Hermite Moment features, with their greatly reduced dimension and efficient representation, has enabled rapid neural training with test with very high classification and low false alarm rate. Experimental demonstration for face recognition and vehicle classification has been successfully carried out using this ATR system.

Paper Details

Date Published: 27 March 1997
PDF: 8 pages
Proc. SPIE 3073, Optical Pattern Recognition VIII, (27 March 1997); doi: 10.1117/12.270376
Show Author Affiliations
Youngchul Park, Jet Propulsion Lab. (United States)
Tien-Hsin Chao, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 3073:
Optical Pattern Recognition VIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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