Paper
22 August 2000 Feasibility of optical detection of land mine trip wires
Stephen K. Babey, John E. McFee, Clifford D. Anger, Avygdor Moise, Stephen Binal Achal
Author Affiliations +
Abstract
Research to assess the feasibility of developing a standoff active or passive optical tripwire detector is discussed. Reflectives of typical tripwires and background materials were measured for UV, VNIR and SWIR wavelengths. A breadboard testbed was developed to obtain images of tripwires against various backgrounds for various geometries and a wide range of VU and VNIR wavelengths. Sample images of simulated and real tripwires in uncluttered environments and against typical cluttered backgrounds were acquired and analyzed. Line detection algorithms were applied to the images to detect tripwires. Although detection was not attempted in real-time, analysis showed that available, cost-effective DSPs could potentially execute those algorithms on the images in real-time. The algorithms successfully detected tripwires in a heavily cluttered background and even have the capability to detect partially obscured wires. To complement the measurements, a spreadsheet model was developed to evaluate the merits of different detectors, sources of illumination, wavebands and geometries for different scenarios. Acceptable signal-to- clutter ratios were found for a number of reasonable passive and active illumination scenarios. The study demonstrated that an optical tripwire detector is feasible in principle.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen K. Babey, John E. McFee, Clifford D. Anger, Avygdor Moise, and Stephen Binal Achal "Feasibility of optical detection of land mine trip wires", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396248
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Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Reflectivity

Ultraviolet radiation

Cameras

Land mines

Detection and tracking algorithms

Signal to noise ratio

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