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Proceedings Paper

Information optimal compressive x-ray threat detection
Author(s): James Huang; Amit Ashok
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Paper Abstract

We present an information-theoretic approach to X-ray measurement design for threat detection in passenger bags. Unlike existing X-ray systems that rely of a large number of sequential tomographic projections for threat detection based on 3D reconstruction, our approach exploits the statistical priors on shape/material of items comprising the bag to optimize multiplexed measurements that can be used directly for threat detection without an intermediate 3D reconstruction. Simulation results show that the optimal multiplexed design achieves higher probability of detection for a given false alarm rate and lower probability of error for a range of exposure (photon) budgets, relative to the non-multiplexed measurements. For example, a 99% detection probability is achieved by optimal multiplexed design requiring 4x fewer measurements than non-multiplexed design.

Paper Details

Date Published: 12 May 2016
PDF: 5 pages
Proc. SPIE 9847, Anomaly Detection and Imaging with X-Rays (ADIX), 98470T (12 May 2016); doi: 10.1117/12.2223784
Show Author Affiliations
James Huang, The Univ. of Arizona (United States)
Amit Ashok, College of Optical Sciences, The Univ. of Arizona (United States)

Published in SPIE Proceedings Vol. 9847:
Anomaly Detection and Imaging with X-Rays (ADIX)
Amit Ashok; Mark A. Neifeld; Michael E. Gehm, Editor(s)

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