Detection of explosive materials in dual-energy X-Ray security systems

Yalçin, Ozan; Reyhancan, İskender Atilla

doi:10.1016/j.nima.2022.167265

Cited by 13 publications

(5 citation statements)

References 9 publications

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“…2. By calculating the linear mass attenuation coefficients (μ and μ') of the materials in the scanned object, the corresponding Zeff values can be determined, which guides the classification of the substances as organic, inorganic, or metallic (Yalçın & Reyhancan, 2022). The dual-energy X-ray systems provide only a single view of the scanned object, which may not be sufficient to identify all potential threats accurately.…”

Section: Literature Reviewmentioning

confidence: 99%

Artificial intelligence technologies utilization for detecting explosive materials

Alshahrani

2024

10.5267/j.ijdns

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Explosive material detection considers the identification and classification of explosive materials using techniques from traditional sniffer dogs to cutting-edge sensing technology like thermal imaging, X-ray scanners, and chemical sensors. Explosive detection is applied in various locations, including airports, government buildings, and public areas, to prevent terrorist attacks and criminal actions that attempt to employ explosive devices. The effectiveness of these procedures is dependent on the detection materials, equipment, and environment, so new techniques are continuously explored to increase precision, sensitivity, and detection speed. Because explosive substances present a critical risk to infrastructure, security, and public safety, extensive analysis of existing detection methods is needed. This paper highlights key areas for further research and development in explosive materials detection by addressing identified limitations and challenges. Specifically, advancements in technology, interdisciplinary collaboration, and the integration of AI techniques offer significant opportunities for improving detection accuracy, reducing false positives, and ensuring safer environments for individuals and society.

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Section: Literature Reviewmentioning

confidence: 99%

Artificial intelligence technologies utilization for detecting explosive materials

Alshahrani

2024

10.5267/j.ijdns

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“…2.2. 14,16 This relationship is unique to the system being studied and can be referred to as the system's characteristic function. The success rates of the 1D-Z ef f model are relatively high, and this model can be used in XSIS.…”

Section: Problem Definitionmentioning

confidence: 99%

“…In addition, studies based on the foundations of physics and aiming at a more robust determination of the effective atomic numbers of objects are prevalent. [11][12][13][14][15][16] These studies utilize the reactions of X-Ray detector cards to the beams passing through the scanned objects. When a beam of light passes through a scanned substance and reaches the detectors, its intensity decreases following the Beer-Lambert rule, which is represented by Eq.…”

Section: Introductionmentioning

confidence: 99%

“…[18][19][20] Then, Z ef f predictions of the objects are made by utilizing the previously obtained characteristic Z ef f -Ratio equation of each system. [14][15][16] As previously mentioned, the Z ef f -R equation varies based on the topology of each system. The unique characteristics of a system's Z ef f -R dynamics are determined by the current and voltage values of the X-Ray tube used, as well as the responses of the detectors to the beam.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, different linear, polynomial, or exponential relationships can be established between Z ef f and R. Based on the performance output, an appropriate Z ef f -R relation can be determined for each system. 14,16 Z ef f = 2.94…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

3D effective atomic number estimation for x-ray security inspection systems

Yalçın

2024

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

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Public places, such as airports, factories, public institutions, and organizations, require advanced security measures. X-Ray systems are often used to check passengers' luggage. Researchers and technologists are constantly working to improve the baggage-checking process by implementing various methods. This study introduces a new method for estimating the effective atomic number. Traditionally, effective atomic number estimation relies on the ratio between high-energy and low-energy images. However, the 3D Effective Atomic Number Estimation model uses high-energy and low-energy image values directly, resolving many issues of the 1D-Ratio model.

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