Paper
21 September 2004 False-alarm mitigation and feature-based discrimination for airborne mine detection
Deepak Menon, Sanjeev Agarwal, Ritesh Ganju, C. W. Swonger
Author Affiliations +
Abstract
The aim of an anomaly detector is to locate spatial target locations that show significantly different spectral/spatial characteristics as compared to the background. Typical anomaly detectors can achieve a high probability of detection, however at the cost of significantly high false alarm rates. For successful minefield detection there is a need for a further processing step to identify mine-like targets and/or reject non-mine targets in order to improve the mine detection to false alarm ratio. In this paper, we discuss a number of false alarm mitigation (FAM) modalities for MWIR imagery. In particular, we investigate measures based on circularity, gray scale shape profile and reflection symmetry. The performance of these modalities is evaluated for false alarm mitigation using real airborne MWIR data at different times of the day and for different spectral bands. We also motivate a feature based clustering and discrimination scheme based on these modalities to classify similar targets. While false alarm mitigation is primarily used to reject non-mine like targets, feature based clustering can be used to select similar-looking mine-like targets. Minefield detection can subsequently proceed on each localized cluster of similar looking targets.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Deepak Menon, Sanjeev Agarwal, Ritesh Ganju, and C. W. Swonger "False-alarm mitigation and feature-based discrimination for airborne mine detection", Proc. SPIE 5415, Detection and Remediation Technologies for Mines and Minelike Targets IX, (21 September 2004); https://doi.org/10.1117/12.544634
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Cited by 5 scholarly publications.
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KEYWORDS
Mining

Target detection

Land mines

Sensors

Metals

Detection and tracking algorithms

Image segmentation

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