Comparison of neutron and high-energy X-ray dual-beam radiography for air cargo inspection

Where are you hiding the pangolins? screening tools to detect illicit contraband at international borders and their adaptability for illegal wildlife trafficking

The illegal movement of wildlife poses a public health, conservation and biosecurity threat, however there are currently minimal screening tools available at international ports of entry to intercept wildlife trafficking efforts. This review first aimed to explore the screening tools available or under development for the detection of concealed wildlife contraband at international ports, including postal services, airlines, road border crossings and maritime routes. Where evidence was deficient, publications detailing the use of methods to uncover other illicit substances, such as narcotics, weapons, human trafficking, explosives, radioactive materials, or special nuclear material, were compiled and assessed for their applicability to the detection of wildlife. The first search identified only four citations related to the detection of wildlife, however the secondary search revealed 145 publications, including 59 journal articles and 86 conference proceedings, describing screening tools for non-wildlife illicit contraband detection. The screening tools uncovered were analysed for potential fitness for purpose for wildlife contraband detection, to evaluate the feasibility of their implementation and their ease of use. The deficiencies evident in terms of resource availability and research efforts targeting wildlife trafficking highlights a potentially substantial national and international security threat which must be addressed.

Modified floating-zone crystal growth of Mg4Ta2O9 and its scintillation performance

Rods of single crystal MgTaO₉ were produced free of macroscopic defects and their scintillation properties including afterglow were measured. The compound characteristics make it a candidate for high energy X-ray radiography applications.

Low-dose material-specific radiography using monoenergetic photons

Cargo containers constitute the most critical component of global trade: 108 million containers represent the movement of about 95% of the world’s manufactured goods. The steady increase in cargo container shipments has had a profound effect on world security: the threat associated with smuggling of shielded special nuclear material is elevated every year. Containers reaching the borders of the U.S. are currently not radiographically inspected due to time and dose considerations stemming from the use of bremsstrahlung beams for imaging. Bremsstrahlung spectra are low-energy peaked, resulting in low penetration values, especially through dense cargoes. The use of monoenergetic radiography beams could alleviate many of these problems due to higher energy and low background continuum. Using Monte Carlo simulations of a realistic imaging scenario with support from previous experimental measurements, we demonstrate how the use of monoenergetic photon beams in radiography can simultaneously reduce the radiation dose imparted to the cargo and any potential stowaways while increasing image quality. Dual-energy methods are leveraged to calculate material atomic number. Image quality is evaluated by measuring the noise standard deviation, contrast-to-noise ratio, and the pixel error as the dose is decreased.

Ferrous and non-ferrous recycling: Challenges and potential technology solutions

Metals recycling is one of the oldest industries in the United States that now employs over 530,000 individuals. It has always played a significant role in the economy, supplied extensive goods and services, and the costs and benefits directly and/or indirectly extend worldwide. Improved efficiency in metals recycling is crucial to achieving a more circular economy; to enable this requires understanding how the industry operates and the challenges it must overcome. Increasing metal product diversity and design complexity combined with increased feed volumes has introduced recent additional challenges. This review explores the current status and state of the industry and examines potential technology solutions that address inbound inspection and material identification challenges.

Measuring and correcting wobble in large-scale transmission radiography

BACKGROUND

Large-scale transmission radiography scanners are used to image vehicles and cargo containers. Acquired images are inspected for threats by a human operator or a computer algorithm. To make accurate detections, it is important that image values are precise. However, due to the scale (∼5 m tall) of such systems, they can be mechanically unstable, causing the imaging array to wobble during a scan. This leads to an effective loss of precision in the captured image.

OBJECTIVE

We consider the measurement of wobble and amelioration of the consequent loss of image precision.

METHODS

Following our previous work, we use Beam Position Detectors (BPDs) to measure the cross-sectional profile of the X-ray beam, allowing for estimation, and thus correction, of wobble. We propose: (i) a model of image formation with a wobbling detector array; (ii) a method of wobble correction derived from this model; (iii) methods for calibrating sensor sensitivities and relative offsets; (iv) a Random Regression Forest based method for instantaneous estimation of detector wobble; and (v) using these estimates to apply corrections to captured images of difficult scenes.

RESULTS

We show that these methods are able to correct for 87% of image error due wobble, and when applied to difficult images, a significant visible improvement in the intensity-windowed image quality is observed.

CONCLUSIONS

The method improves the precision of wobble affected images, which should help improve detection of threats and the identification of different materials in the image.

Automated X-ray image analysis for cargo security: Critical review and future promise

We review the relatively immature field of automated image analysis for X-ray cargo imagery. There is increasing demand for automated analysis methods that can assist in the inspection and selection of containers, due to the ever-growing volumes of traded cargo and the increasing concerns that customs- and security-related threats are being smuggled across borders by organised crime and terrorist networks. We split the field into the classical pipeline of image preprocessing and image understanding. Preprocessing includes: image manipulation; quality improvement; Threat Image Projection (TIP); and material discrimination and segmentation. Image understanding includes: Automated Threat Detection (ATD); and Automated Contents Verification (ACV). We identify several gaps in the literature that need to be addressed and propose ideas for future research. Where the current literature is sparse we borrow from the single-view, multi-view, and CT X-ray baggage domains, which have some characteristics in common with X-ray cargo.

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning

BACKGROUND

Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become more stringent, manual inspection by trained operators is less and less viable due to low throughput. Machine vision techniques can assist operators in their task by automating parts of the inspection workflow. Since cars are routinely involved in trafficking, export fraud, and tax evasion schemes, they represent an attractive target for automated detection and flagging for subsequent inspection by operators.

OBJECTIVE

Development and evaluation of a novel method for the automated detection of cars in complex X-ray cargo imagery.

METHODS

X-ray cargo images from a stream-of-commerce dataset were classified using a window-based scheme. The limited number of car images was addressed by using an oversampling scheme. Different Convolutional Neural Network (CNN) architectures were compared with well-established bag of words approaches. In addition, robustness to concealment was evaluated by projection of objects into car images.

RESULTS

CNN approaches outperformed all other methods evaluated, achieving 100% car image classification rate for a false positive rate of 1-in-454. Cars that were partially or completely obscured by other goods, a modus operandi frequently adopted by criminals, were correctly detected.

CONCLUSIONS

We believe that this level of performance suggests that the method is suitable for deployment in the field. It is expected that the generic object detection workflow described can be extended to other object classes given the availability of suitable training data.

Radioisotopes produced by neutron irradiation of food

The use of neutrons for cargo interrogation has the potential to drastically improve threat detection. Previous research has focussed on the production of (24)Na, based on the isotopes produced in pharmaceuticals and medical devices. For both the total activity and the ingestion dose we show that a variety of isotopes contribute and that (24)Na is only dominant under certain conditions. The composition of the foods has a strong influence on the resulting activity and ingestion dose suggesting that the pharmaceuticals and medical devices considered initially are not a viable analogue for foodstuffs. There is an energy dependence to the isotopes produced due to the cross-sections of different reactions varying with neutron energy. We show that this results in different isotopes dominating the ingestion dose at different energies, which has not been considered in the previous literature.

Radiography with cosmic-ray and compact accelerator muons; Exploring inner-structure of large-scale objects and landforms

Cosmic-ray muons (CRM) arriving from the sky on the surface of the earth are now known to be used as radiography purposes to explore the inner-structure of large-scale objects and landforms, ranging in thickness from meter to kilometers scale, such as volcanic mountains, blast furnaces, nuclear reactors etc. At the same time, by using muons produced by compact accelerators (CAM), advanced radiography can be realized for objects with a thickness in the sub-millimeter to meter range, with additional exploration capability such as element identification and bio-chemical analysis. In the present report, principles, methods and specific research examples of CRM transmission radiography are summarized after which, principles, methods and perspective views of the future CAM radiography are described.

Radiography simulation on single-shot dual-spectrum X-ray for cargo inspection system

We propose a method to identify materials in the dual energy X-ray (DeX) inspection system. This method identifies materials by combining information on the relative proportions T of high-energy and low-energy X-rays transmitted through the material, and the ratio R of the attenuation coefficient of the material when high-energy are used to that when low energy X-rays are used. In Monte Carlo N-Particle Transport Code (MCNPX) simulations using the same geometry as that of the real container inspection system, this T vs. R method successfully identified tissue-equivalent plastic and several metals. In further simulations, the single-shot mode of operating the accelerator led to better distinguishing of materials than the dual-shot system.