Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage
Abstract
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.
- Inventors:
- Issue Date:
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1924946
- Patent Number(s):
- 11403765
- Application Number:
- 16/540,610
- Assignee:
- Lawrence Livermore National Security, LLC (Livermore, CA)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01V - GEOPHYSICS
G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- DOE Contract Number:
- AC52-07NA27344
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 08/14/2019
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Paglieroni, David W., Pechard, Christian T., and Martz, Jr., Harry E. Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage. United States: N. p., 2022.
Web.
Paglieroni, David W., Pechard, Christian T., & Martz, Jr., Harry E. Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage. United States.
Paglieroni, David W., Pechard, Christian T., and Martz, Jr., Harry E. Tue .
"Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage". United States. https://www.osti.gov/servlets/purl/1924946.
@article{osti_1924946,
title = {Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage},
author = {Paglieroni, David W. and Pechard, Christian T. and Martz, Jr., Harry E.},
abstractNote = {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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {8}
}
Works referenced in this record:
Deriving effective atomic numbers from DECT based on a parameterization of the ratio of high and low linear attenuation coefficients
journal, September 2013
- Landry, Guillaume; Seco, Joao; Gaudreault, Mathieu
- Physics in Medicine and Biology, Vol. 58, Issue 19
Method to Extract System-Independent Material Properties From Dual-Energy X-Ray CT
journal, March 2019
- Champley, Kyle M.; Azevedo, Stephen G.; Seetho, Isaac M.
- IEEE Transactions on Nuclear Science, Vol. 66, Issue 3
U-Net: Convolutional Networks for Biomedical Image Segmentation
book, November 2015
- Ronneberger, Olaf; Fischer, Philipp; Brox, Thomas
- Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III
Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests
journal, June 2016
- Gao, Yaozong; Shao, Yeqin; Lian, Jun
- IEEE Transactions on Medical Imaging, Vol. 35, Issue 6
Method Of And System For Splitting Compound Objects In Multi-energy Computed Tomography Images
patent-application, January 2007
- Simanovsky, Sergey; Ying, Zhengrong; Crawford, Carl R.
- US Patent Application 11/183378; 20070014471
Terahertz imaging system for examining articles
patent-application, October 2007
- Zimdars, David A.; Stuk, Greg; Williamson, Steven L.
- US Patent Application 11/138246; 20070235658
Systems and methods for image processing
patent-application, February 2020
- Dujmic, Denis
- US Patent Application 16/537417; 20200051017
System-Independent Characterization of Materials Using Dual-Energy Computed Tomography
journal, February 2016
- Azevedo, Stephen G.; Martz, Harry E.; Aufderheide, Maurice B.
- IEEE Transactions on Nuclear Science, Vol. 63, Issue 1
Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery
conference, December 2019
- Gaus, Yona Falinie A.; Bhowmik, Neelanjan; Akcay, Samet
- 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)
Verifying object measurements determined from mobile device images
patent, November 2016
- Boardman, David; Clipp, Brian Sanderson; Erignac, Charles A.
- US Patent Document 9,495,764
Systems and methods for imaging and detecting sheet-like material
patent-application, January 2014
- Basu, Samit; Gable, Todd Jason
- US Patent Application 13/542732; 20140010342
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods
journal, November 2012
- Achanta, R.; Shaji, A.; Smith, K.
- IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, Issue 11, p. 2274-2282
Method and apparatus for automatic image quality assessment
patent, November 2004
- Karimi, Seemeen S.; Rozas, David; Simanovsky, Sergey
- US Patent Document 6,813,374
Object detection methods, display methods and apparatuses
patent-application, November 2015
- Zhang, Li; Chen, Zhiqiang; Zhao, Ziran
- US Patent Application 14/138399; 20150332448
Methods and systems for non-cooperative automatic security screening in crowded areas
patent-application, September 2017
- Kuznetsov, Andrey; Meshcheryakov, Viktor; Semenov, Semen
- US Patent Application 15/613832; 20170270366
Systems and methods for detecting luggage in an imaging system
patent-application, December 2017
- Basu, Samit Kumar
- US Patent Application 15/188440; 20170365074
Method and System for Electronic Inspection of Baggage and Cargo
patent-application, February 2010
- Song, Samuel Moon-Ho; Boyd, Douglas Perry
- US Patent Application 12/197,687; 2010/0046704 Al
Method and system for blood vessel segmentation and classification
patent-application, November 2010
- Ostrovsky-Berman, Yaron; Porat, Hadar; Gazit, Tiferet Ahavah
- US Patent Application 12/781836; 20100296709