Counterterrorist detection techniques of explosives by vapor sensors (handheld)

Kagan, Avi

doi:10.1016/b978-0-444-64104-5.00012-6

Cited by 5 publications

(3 citation statements)

References 59 publications

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“…This can then be used to produce a material-specific XRD form factor that can be used for identification. This additional information can prove incredibly useful when attempting to classify materials [1,6].…”

Section: Orthogonality and Physicsmentioning

confidence: 99%

“…This allows for authorities to keep potentially harmful items, such as weapons, and energetics, such as explosives, away from accessible areas of passenger aircraft. Security screening has been the preferred methodology for many airports and regulators to achieve this goal, and over the last few decades, the technology employed in this effort has evolved to meet new standards of performance [1].…”

Section: Introductionmentioning

confidence: 99%

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Performance of a high-throughput full-tunnel XRD checked baggage scanning system

Coccarelli¹,

Dudley²,

Pike³

et al. 2023

Anomaly Detection and Imaging With X-Rays (ADIX) VIII

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X-ray diffraction imaging (XRDI) offers the potential for reduced false alarm rates, increased throughputs, and more sensitive explosives detection performance in aviation security applications. The deployment of computed tomography (CT) systems across carry-on and checked baggage screening lanes has both reinforced the need for orthogonal detection technologies and created an exciting new opportunity for the implementation of XRDI. Our team at Quadridox built a novel XRDI system that, when combined with a CT system, realizes full-tunnel assessment of checked bags at a belt speed of 20 cm/s. We integrated our XRDI system with a Smiths CTX 5800 explosives detection system (EDS) and collected bag data containing both benign and threat objects. We describe the XRDI system, show examples of the resulting hybrid CT and XRD dataset, and present performance results for the hybrid system.

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Section: Orthogonality and Physicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance of a high-throughput full-tunnel XRD checked baggage scanning system

Coccarelli¹,

Dudley²,

Pike³

et al. 2023

Anomaly Detection and Imaging With X-Rays (ADIX) VIII

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show abstract

“…Computed tomography (CT) is a non-destructive X-ray technique used to probe the internal morphological structure of objects [1,2]. It plays a pivotal role in diverse fields such as medicine [3][4][5], industry [6][7][8], safety protocols [9,10], and scientific exploration, particularly in scrutinizing the morphology of promising functional materials [11]. Despite over 80 years of development in computed tomography algorithms [12,13], the pursuit of innovation and optimization remains ongoing.…”

Section: Introduction 1problem Relevancementioning

confidence: 99%

Tomographic Reconstruction: General Approach to Fast Back-Projection Algorithms

Polevoy,

Gilmanov,

Kazimirov

et al. 2023

Mathematics

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Addressing contemporary challenges in computed tomography (CT) demands precise and efficient reconstruction. This necessitates the optimization of CT methods, particularly by improving the algorithmic efficiency of the most computationally demanding operators—forward projection and backprojection. Every measurement setup requires a unique pair of these operators. While fast algorithms for calculating forward projection operators are adaptable across various setups, they fall short in three-dimensional scanning scenarios. Hence, fast algorithms are imperative for backprojection, an integral aspect of all established reconstruction methods. This paper introduces a general method for the calculation of backprojection operators in any measurement setup. It introduces a versatile method for transposing summation-based algorithms, which rely exclusively on addition operations. The proposed approach allows for the transformation of algorithms designed for forward projection calculation into those suitable for backprojection, with the latter maintaining asymptotic algorithmic complexity. Employing this method, fast algorithms for both forward projection and backprojection have been developed for the 2D few-view parallel-beam CT as well as for the 3D cone-beam CT. The theoretically substantiated complexity values for the proposed algorithms align with their experimentally derived estimates.

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Multi-Energy and Fast-Convergence Iterative Reconstruction Algorithm for Organic Material Identification Using X-ray Computed Tomography

et al. 2023

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In order to significantly reduce the computing time while, at the same time, keeping the accuracy and precision when determining the local values of the density and effective atomic number necessary for identifying various organic material, including explosives and narcotics, a specialized multi-stage procedure based on a multi-energy computed tomography investigation within the 20–160 keV domain was elaborated. It consisted of a compensation for beam hardening and other non-linear effects that affect the energy dependency of the linear attenuation coefficient (LAC) in the chosen energy domain, followed by a 3D fast reconstruction algorithm capable of reconstructing the local LAC values for 64 energy values from 19.8 to 158.4 keV, and, finally, the creation of a set of algorithms permitting the simultaneous determination of the density and effective atomic number of the investigated materials. This enabled determining both the density and effective atomic number of complex objects in approximately 24 s, with an accuracy and precision of less than 3%, which is a significantly better performance with respect to the reported literature values.

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Counterterrorist detection techniques of explosives by vapor sensors (handheld)

Cited by 5 publications

References 59 publications

Performance of a high-throughput full-tunnel XRD checked baggage scanning system

Performance of a high-throughput full-tunnel XRD checked baggage scanning system

Tomographic Reconstruction: General Approach to Fast Back-Projection Algorithms

Multi-Energy and Fast-Convergence Iterative Reconstruction Algorithm for Organic Material Identification Using X-ray Computed Tomography

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