20 June 1995 Identifying minefields in clutter via collinearity and regularity detection
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Abstract
Detecting minefields in the presence of clutter is an important challenge for the Navy. Minefields have point patterns that tend to exhibit regularity such as equal-spacing and collinearity that provide potentially valuable discriminants against natural occuring clutter. These tendencies arise because of a variety of compelling factors including strategic doctrine, safety, tactical and economic efficiency, and perhaps most intriguing, the human element. In this paper, we introduce several simple procedures to detect regularity in point proceses including the empty boxes test (EBT) and its extensions, the skeptical likelihood test (SLT), and a Fourier-based method. Several possible methods to specifically detect collinearity are also discussed. The preliminary detection performance of a variety of these minefield detection methods are investigated using simulated data and a point pattern extracted from real sensor data.
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Douglas E. Lake, Daniel M. Keenan, "Identifying minefields in clutter via collinearity and regularity detection", Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211348; https://doi.org/10.1117/12.211348
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KEYWORDS
Sensors

Molybdenum

Image processing

Land mines

Data modeling

Image filtering

Safety

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