Automatic classification of unexploded ordnance applied to live sites for MetalMapper sensor

John Brevard Sigman; Kevin O'Neill; Benjamin Barrowes; Yinlin Wang; Fridon Shubitidze

doi:10.1117/12.2050784

9 June 2014 Automatic classification of unexploded ordnance applied to live sites for MetalMapper sensor

John Brevard Sigman, Kevin O'Neill, Benjamin Barrowes, Yinlin Wang, Fridon Shubitidze

Proceedings Volume 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX; 90720F (2014) https://doi.org/10.1117/12.2050784
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

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.

Citation Download Citation

John Brevard Sigman, Kevin O'Neill, Benjamin Barrowes, Yinlin Wang, and Fridon Shubitidze "Automatic classification of unexploded ordnance applied to live sites for MetalMapper sensor", Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 90720F (9 June 2014); https://doi.org/10.1117/12.2050784

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available