X-ray baggage scanners play a basic role in the protection of airports, customs, and other strategically important buildings and infrastructures. The current technology of baggage scanners is based on x-ray attenuation, meaning that the detection of threat objects relies on how various objects differently attenuate the x-ray beams going through them. This capability is enhanced by the use of dual-energy x-ray scanners, which make the determination of the x-ray attenuation characteristics of a material more precise by taking images with different x-ray spectra, and combining the information appropriately. However, this still has limitations whenever objects with similar attenuation characteristics have to be distinguished. We describe an alternative approach based on a different x-ray interaction phenomenon, x-ray refraction. Refraction is a familiar phenomenon in visible light (e.g., what makes a straw half immersed in a glass of water appear bent), which also takes place in the x-ray regime, only causing deviations at much smaller angles. Typically, these deviations occur at the boundaries of all objects. We have developed a system that, like other "phase contrast" based instruments, is capable of detecting such deviations, and therefore of creating precise images of the contours of all objects. This complements the material-related information provided by x-ray attenuation, and helps contextualizing the nature of the individual objects, therefore resulting in an increase of both sensitivity (increased detection rate) and specificity (reduced rate of false positives) of baggage scanners.
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http://dx.doi.org/10.3390/ma4101846 | DOI Listing |
Sci Justice
September 2022
Cranfield Forensic Institute, Cranfield University, College Road, Cranfield MK43 0AL, United Kingdom.
The need to forensically search soil for small artefacts at a burial site or traces of evidence in a deposition site is a common task shared by investigators and forensic archaeologists. In forensic casework, the importance of finding small pieces of evidence, such as personal effects or ballistic fragments, cannot be overstated as it can assist in the positive identification of the deceased, give an insight into the manner and cause of death, and identify any perpetrators. The soil search methods known as wet and dry sieving, are cumbersome, time-consuming and have limited success for some soil types.
View Article and Find Full Text PDFJ Xray Sci Technol
October 2021
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA.
Background: Materials characterization made possible by dual energy CT (DECT) scanners is expected to considerably improve automatic detection of hazardous objects in checked and carry-on luggage at our airports. Training a computer to identify the hazardous items from DECT scans however implies training on a baggage dataset that can represent all the possible ways a threat item can packed inside a bag. Practically, however, generating such data is made challenging by the logistics (and the permissions) related to the handling of the hazardous materials.
View Article and Find Full Text PDFSensors (Basel)
November 2020
Center for Cyber-Physical Systems, Khalifa University of Science and Technology, Abu Dhabi 127788, UAE.
Screening baggage against potential threats has become one of the prime aviation security concerns all over the world, where manual detection of prohibited items is a time-consuming and hectic process. Many researchers have developed autonomous systems to recognize baggage threats using security X-ray scans. However, all of these frameworks are vulnerable against screening cluttered and concealed contraband items.
View Article and Find Full Text PDFJ Xray Sci Technol
May 2021
Department of Computer Science, Durham University, UK.
Background: The screening of baggage using X-ray scanners is now routine in aviation security with automatic threat detection approaches, based on 3D X-ray computed tomography (CT) images, known as Automatic Threat Recognition (ATR) within the aviation security industry. These current strategies use pre-defined threat material signatures in contrast to adaptability towards new and emerging threat signatures. To address this issue, the concept of adaptive automatic threat recognition (AATR) was proposed in previous work.
View Article and Find Full Text PDFInt J Legal Med
July 2020
Cranfield Forensic Institute, Defence Academy of the United Kingdom, Cranfield University, Shrivenham, SN6 8LA, UK.
Disaster victim identification following a mass fatality incident is focussed on identifying the deceased and returning them to their families as quickly as possible, while gathering as much information as practical to aid investigators in establishing the cause of the incident. Ante-mortem data is gathered and compared with the post-mortem data obtained in order to positively identify the deceased. This paper presents results from a study concerned with the first part of the process of identifying the deceased-the triage or Primary Survey and how this can be done without access to hospital facilities such as conventional X-ray imaging or computed tomography.
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