Consensus relaxation on materials of interest for adaptive ATR in CT images of baggage

David W. Paglieroni; Hema Chandrasekaran; Christian Pechard; Harry E. Martz Jr.

doi:10.1117/12.2309839

27 April 2018 Consensus relaxation on materials of interest for adaptive ATR in CT images of baggage

David W. Paglieroni, Hema Chandrasekaran, Christian Pechard, Harry E. Martz Jr.

Proceedings Volume 10632, Anomaly Detection and Imaging with X-Rays (ADIX) III; 106320E (2018) https://doi.org/10.1117/12.2309839
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

An adaptive automatic threat recognition system (AATR) developed at the Lawrence Livermore National Laboratory (LLNL) is described for x-ray CT images of baggage. The AATR automatically adapts to the input object requirement specification (ORS), which can change or evolve over time. These specifications characterize materials of interest (MOIs), basic physical features of interest (FOIs) (such a mass and thickness) and performance goals (detection and false alarm probability) for objects of interest (OOIs). The need and technical requirements for an AATR were developed in collaboration with DHS’s Explosives Division and Northeastern University’s Awareness and Localization of Explosives-Related Threats (ALERT) Center, a DHS Center of Excellence (http://www.northeastern.edu/alert/). Independent of the input ORS, LLNL’s AATR always uses the same algorithm and codes to process CT images. The algorithm adapts in real-time to changes in the input ORS. LLNL’s AATR is thus suitable for dynamic scenarios in which the nature of the OOIs can change rapidly. The AATR uses a spatial consensus relaxation method to determine the most likely material composition for each CT image voxel. The resulting image of most likely material compositions is segmented. An OOI classification statistic (OOI score) is computed for each voxel and each extracted image volume. OOI recognition performance is reported using various metrics on a test set of ~180 plastic bins supplied by the ALERT Center of Excellence. A method is then proposed for automatic decision threshold estimation that can adapt to the detection performance goal, the most likely material composition, and the contents of the baggage.

Conference Presentation

Citation Download Citation

David W. Paglieroni, Hema Chandrasekaran, Christian Pechard, and Harry E. Martz Jr. "Consensus relaxation on materials of interest for adaptive ATR in CT images of baggage", Proc. SPIE 10632, Anomaly Detection and Imaging with X-Rays (ADIX) III, 106320E (27 April 2018); https://doi.org/10.1117/12.2309839

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