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18 October 2001 Development of a robust algorithm for detection of mine targets in image data from electro-optic and acoustic sensors
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Abstract
Current minefield detection research indicates that operationally no single sensor technology will likely be capable of detecting mines/minefields in a real-time manner and at a performance level suitable for a forward maneuver unit. Minefield detection involves a particularly wide range of operating scenarios and environmental conditions, which requires deployment of complementary sensor suites. We have focused, therefore, on the development of a computationally efficient and robust detection algorithm that exploits robust image processing techniques centered on meaningful target feature sets applicable to a variety of imaging sensors. This paper presents the detection technique, emphasizing its robust architecture, and provides performance results for image data generated by complementary sensors. The paper also briefly discusses the application of this detector as a component of fusion architectures for processing returns form diverse imaging sensors, including multi-channel image data from disparate sensors.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arnold C. Williams, Rodney P. Meyer, Peter W. Pachowicz, George B. Maksymonko, Thomas R. Witten, and James D. Habersat "Development of a robust algorithm for detection of mine targets in image data from electro-optic and acoustic sensors", Proc. SPIE 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI, (18 October 2001); https://doi.org/10.1117/12.445422
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