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Proceedings Paper

Recognition using wavelets for use with a mobile robot explorer
Author(s): Lynne L. Grewe; Jader Filho; Yutaka Kanayama
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Paper Abstract

In this paper, we describe a wavelet-based vision system created to detect unexploded ordnances (UXOs). This system was created to test whether or not a vision system could be a useful component on a mobile robot platform whose purpose is the exploration of possibly unknown environments for the detection of UXOs. As a first phase, we describe here, the extraction of relatively simple features in the wavelet domain. We capitalize upon the fact that the wavelet domain is multiresolutional in nature, and compactly represents local frequency information in the feature extraction phase. These features are used in a neural network system for the purpose of recognition. Results show that these features perform well for localization, but, suggest additional features are needed for identification. This work compliments other ongoing research in UXO detection at the Naval PostGraduate School. In the past, magnetometer readings have been used for underground UXO detection. A possible avenue of future research is to create a multi- sensor system using visual, magnetometer and possibly other data to arrive at better decisions.

Paper Details

Date Published: 26 March 1998
PDF: 7 pages
Proc. SPIE 3391, Wavelet Applications V, (26 March 1998); doi: 10.1117/12.304913
Show Author Affiliations
Lynne L. Grewe, California State Univ./Monterey Bay and Naval Postgraduate School (United States)
Jader Filho, Naval Postgraduate School (United States)
Yutaka Kanayama, Naval Postgraduate School (United States)


Published in SPIE Proceedings Vol. 3391:
Wavelet Applications V
Harold H. Szu, Editor(s)

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