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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2014/42777
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| Title: | Composite wavelet filters for enhanced automated target recognition |
| Authors: | Chiang, Jeffrey N.
Zhang, Yuhan
Lu, Thomas T.
Chao, Tien-Hsin |
| Keywords: | automated target recognition
wavelet filter
sonar video image processing |
| Issue Date: | 27-Apr-2012 |
| Publisher: | Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2012. |
| Citation: | SPIE Symposium on Defense, Security, and Sensing, Baltimore, Maryland, April 23-27, 2012 |
| 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 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. |
| URI: | http://hdl.handle.net/2014/42777 |
| Appears in Collections: | JPL TRS 1992+
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