Information optimal compressive x-ray threat detection

James Huang, Amit Ashok

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationAnomaly Detection and Imaging with X-Rays (ADIX)
EditorsMichael E. Gehm, Amit Ashok, Mark A. Neifeld
ISBN (Electronic)9781510600881
StatePublished - 2016
EventAnomaly Detection and Imaging with X-Rays (ADIX) Conference - Baltimore, United States
Duration: Apr 19 2016Apr 20 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherAnomaly Detection and Imaging with X-Rays (ADIX) Conference
Country/TerritoryUnited States


  • Compressive sensing
  • Information theory
  • Multiplex
  • Threat detection
  • Tomography
  • X-ray

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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