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Proceedings Paper

Application of Bayesian statistical analysis to illicit substance detection using nondestructive interrogation techniques
Author(s): Leonid Sagalovsky; Donald L. Smith; Bradley J. Micklich; Charles L. Fink; Thomas J. Yule
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Paper Abstract

Non-destructive interrogation systems designed to locate illicit substances in sealed containers involve decision making when the available objective information is incomplete. The greater the quantity of information, the more reliable is the determination of the unknown content. Therefore, it is important to be able to utilize all possible measured data pertaining to the unknown object. Among the data which can be considered are x-ray measurements, fast-neutron transmission measurements, cargo manifest data and, possibly, information of a physical, chemical or even psychological nature. The Bayesian approach provides a statistical framework for merging diverse information about any object, including a priori knowledge, subjective knowledge and objective knowledge gained from current measurements. This paper outlines the fundamental principles of Bayesian analysis and explores possible applications to the detection of illicit substances.

Paper Details

Date Published: 27 February 1997
PDF: 4 pages
Proc. SPIE 2867, International Conference Neutrons in Research and Industry, (27 February 1997); doi: 10.1117/12.267906
Show Author Affiliations
Leonid Sagalovsky, Argonne National Lab. (United States)
Donald L. Smith, Argonne National Lab. (United States)
Bradley J. Micklich, Argonne National Lab. (United States)
Charles L. Fink, Argonne National Lab. (United States)
Thomas J. Yule, Argonne National Lab. (United States)

Published in SPIE Proceedings Vol. 2867:
International Conference Neutrons in Research and Industry
George Vourvopoulos, Editor(s)

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