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Proceedings Paper

Automatic classification of unexploded ordnance applied to live sites for MetalMapper sensor
Author(s): John Brevard Sigman; Kevin O'Neill; Benjamin Barrowes; Yinlin Wang; Fridon Shubitidze
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Paper Abstract

This paper extends a previously-introduced method for automatic classification of Unexploded Ordnance (UXO) across several datasets from live sites. We used the MetalMapper sensor, from which extrinsic and intrinsic parameters are determined by the combined Differential Evolution (DE) and Ortho-Normalized Volume Magnetic Source (ONVMS) algorithms. The inversion provides spatial locations and intrinsic time-series total ONVMS principal eigenvalues. These are fit to a power-decay empirical model, providing dimensionality reduction to 3 coefficients (k, b, and g) for polarizability decay. Anomaly target features are grouped using the unsupervised clustering Weighted-Pair Group Method with Averaging (WPGMA) algorithm. Central elements of each cluster are dug, and the results are used to train the next round of dig requests. A Naive Bayes classifier is used as a supervised learning algorithm, in which the product of each feature's independent probability density represents each class of UXO in the feature space. We request ground truths for anomalies in rounds, until there are no more Targets of Interest (TOI) in consecutive requests. This fully automatic procedure requires no expert intervention, saving time and money. Naive Bayes outperformed previous efforts with Gaussian Mixture Models(GMM) in all cases.

Paper Details

Date Published: 9 June 2014
PDF: 7 pages
Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 90720F (9 June 2014); doi: 10.1117/12.2050784
Show Author Affiliations
John Brevard Sigman, Dartmouth College (United States)
Kevin O'Neill, Dartmouth College (United States)
Benjamin Barrowes, U.S. Army Engineer Research and Engineering Ctr. (United States)
Yinlin Wang, Dartmouth College (United States)
Fridon Shubitidze, Dartmouth College (United States)

Published in SPIE Proceedings Vol. 9072:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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