Composite wavelet filters for enhanced automated target recognition

Jeffrey N. Chiang; Yuhan Zhang; Thomas T. Lu; Tien-Hsin Chao

doi:10.1117/12.923482

23 April 2012 Composite wavelet filters for enhanced automated target recognition

Jeffrey N. Chiang, Yuhan Zhang, Thomas T. Lu, Tien-Hsin Chao

Proceedings Volume 8398, Optical Pattern Recognition XXIII; 83980E (2012) https://doi.org/10.1117/12.923482
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater were unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

Citation Download Citation

Jeffrey N. Chiang, Yuhan Zhang, Thomas T. Lu, and Tien-Hsin Chao "Composite wavelet filters for enhanced automated target recognition", Proc. SPIE 8398, Optical Pattern Recognition XXIII, 83980E (23 April 2012); https://doi.org/10.1117/12.923482

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