Automatic target recognition processor using an optical wavelet preprocessor and an electronic neural classifier

Youngchul Park; Tien-Hsin Chao

doi:10.1117/12.270376

27 March 1997 Automatic target recognition processor using an optical wavelet preprocessor and an electronic neural classifier

Youngchul Park, Tien-Hsin Chao

Author Affiliations +

Proceedings Volume 3073, Optical Pattern Recognition VIII; (1997) https://doi.org/10.1117/12.270376
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

Youngchul Park and Tien-Hsin Chao "Automatic target recognition processor using an optical wavelet preprocessor and an electronic neural classifier", Proc. SPIE 3073, Optical Pattern Recognition VIII, (27 March 1997); https://doi.org/10.1117/12.270376

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