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Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage

Patent ·
OSTI ID:1924946
; ;
An automatic threat recognition (ATR) system is disclosed for scanning an article to recognize contraband items or items of interest contained within the article. The ATR system uses a CAT scanner to obtain a CT image scan of objects within the article, representing a plurality of 2D image slices of the article and its contents. Each 2D image slice includes information forming a plurality of voxels. The ATR system includes a computer and determines which voxels have a likelihood of representing materials of interest. It then aggregates those voxels to produce detected objects. The detected objects are further classified as items of interest vs. not of interest. The ATR system is based on learned parameters for a novel interaction of global and object context mechanisms. ATR system performance may be optimized by using jointly optimal global and object context parameters learned during training. The global context parameters may apply to the article as a whole and facilitate object detection. The object context parameters may apply to the individual object detections.
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC52-07NA27344
Assignee:
Lawrence Livermore National Security, LLC (Livermore, CA)
Patent Number(s):
11,403,765
Application Number:
16/540,610
OSTI ID:
1924946
Country of Publication:
United States
Language:
English

References (10)

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Deriving effective atomic numbers from DECT based on a parameterization of the ratio of high and low linear attenuation coefficients journal September 2013
Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery conference December 2019
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ZeCalc Algorithm Details report January 2013

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