Optimization of a multi-stage ATR system for small target identification

Tsung Han (Hank) Lin; Thomas Lu; Henry Braun; Weston Edens; Yuhan Zhang; Tien-Hsin Chao; Christopher Assad; Terrance Huntsberger

doi:10.1117/12.858165

7 May 2010 Optimization of a multi-stage ATR system for small target identification

Tsung Han (Hank) Lin, Thomas Lu, Henry Braun, Weston Edens, Yuhan Zhang, Tien-Hsin Chao, Christopher Assad, Terrance Huntsberger

Author Affiliations +

Proceedings Volume 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI; 76961Y (2010) https://doi.org/10.1117/12.858165
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

An Automated Target Recognition system (ATR) was developed to locate and target small object in images and videos. The data is preprocessed and sent to a grayscale optical correlator (GOC) filter to identify possible regionsof- interest (ROIs). Next, features are extracted from ROIs based on Principal Component Analysis (PCA) and sent to neural network (NN) to be classified. The features are analyzed by the NN classifier indicating if each ROI contains the desired target or not. The ATR system was found useful in identifying small boats in open sea. However, due to "noisy background," such as weather conditions, background buildings, or water wakes, some false targets are mis-classified. Feedforward backpropagation and Radial Basis neural networks are optimized for generalization of representative features to reduce false-alarm rate. The neural networks are compared for their performance in classification accuracy, classifying time, and training time.

Citation Download Citation

Tsung Han (Hank) Lin, Thomas Lu, Henry Braun, Weston Edens, Yuhan Zhang, Tien-Hsin Chao, Christopher Assad, and Terrance Huntsberger "Optimization of a multi-stage ATR system for small target identification", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76961Y (7 May 2010); https://doi.org/10.1117/12.858165

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