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Proceedings Paper

Road detection and buried object detection in elevated EO/IR imagery
Author(s): Levi Kennedy; Mark P. Kolba; Joshua R. Walters
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Paper Abstract

To assist the warfighter in visually identifying potentially dangerous roadside objects, the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) has developed an elevated video sensor system testbed for data collection. This system provides color and mid-wave infrared (MWIR) imagery. Signal Innovations Group (SIG) has developed an automated processing capability that detects the road within the sensor field of view and identifies potentially threatening buried objects within the detected road. The road detection algorithm leverages system metadata to project the collected imagery onto a flat ground plane, allowing for more accurate detection of the road as well as the direct specification of realistic physical constraints in the shape of the detected road. Once the road has been detected in an image frame, a buried object detection algorithm is applied to search for threatening objects within the detected road space. The buried object detection algorithm leverages textural and pixel intensity-based features to detect potential anomalies and then classifies them as threatening or non-threatening objects. Both the road detection and the buried object detection algorithms have been developed to facilitate their implementation in real-time in the NVESD system.

Paper Details

Date Published: 10 May 2012
PDF: 9 pages
Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 83570S (10 May 2012); doi: 10.1117/12.921124
Show Author Affiliations
Levi Kennedy, Signal Innovations Group, Inc. (United States)
Mark P. Kolba, Signal Innovations Group, Inc. (United States)
Joshua R. Walters, Signal Innovations Group, Inc. (United States)

Published in SPIE Proceedings Vol. 8357:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII
J. Thomas Broach; John H. Holloway Jr., Editor(s)

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