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Proceedings Paper

Composite wavelet filters for enhanced automated target recognition
Author(s): Jeffrey N. Chiang; Yuhan Zhang; Thomas T. Lu; Tien-Hsin Chao
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Paper 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.

Paper Details

Date Published: 23 April 2012
PDF: 10 pages
Proc. SPIE 8398, Optical Pattern Recognition XXIII, 83980E (23 April 2012); doi: 10.1117/12.923482
Show Author Affiliations
Jeffrey N. Chiang, Univ. of California, Los Angeles (United States)
Yuhan Zhang, Onescreen Inc. (United States)
Thomas T. Lu, Jet Propulsion Lab. (United States)
Tien-Hsin Chao, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 8398:
Optical Pattern Recognition XXIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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