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Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONARAutomated 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 Underwater Vehicles (UUVs). 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 report.

Document ID
20150006587
Acquisition Source
Jet Propulsion Laboratory
Document Type
Other
External Source(s)
Authors
Chiang, Jeffrey N.
(California Univ. Los Angeles, CA, United States)
Date Acquired
April 23, 2015
Publication Date
August 1, 2011
Subject Category
Instrumentation And Photography
Distribution Limits
Public
Copyright
Other
Keywords
image processing
Automated target recognition (ATR)

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