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Composite Wavelet Filters for Enhanced Automated Target RecognitionAutomated 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 are 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 paper.
Document ID
Document Type
Conference Paper
External Source(s)
Chiang, Jeffrey N.
(California Univ. Los Angeles, CA, United States)
Zhang, Yuhan
(OneScreen, Inc. Irvine, CA, United States)
Lu, Thomas T.
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Chao, Tien-Hsin
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 27, 2013
Publication Date
April 27, 2012
Subject Category
Instrumentation And Photography
Meeting Information
SPIE Symposium on Defense, Security, and Sensing(Baltimore, MD)
Distribution Limits
automated target recognition
sonar video image processing
wavelet filter

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