Detecting Electric Devices in 3D Images of Bags
Anthony Bagnall, Paul Southam, James Large, Richard Harvey

TL;DR
This paper introduces UXPR, an automated method for detecting electrical devices in 3D baggage scans using segmentation, prediction, and ensemble techniques, enhancing security screening efficiency and accuracy.
Contribution
The paper presents a novel algorithm, UXPR, for automated detection of electrical devices in 3D luggage scans, combining segmentation, classification, and ensemble methods.
Findings
High detection rate for known device types
Promising results for unseen device detection
Effective segmentation and classification in 3D scans
Abstract
The aviation and transport security industries face the challenge of screening high volumes of baggage for threats and contraband in the minimum time possible. Automation and semi-automation of this procedure offers the potential to increase security by detecting more threats and improve the customer experience by speeding up the process. Traditional 2D x-ray images are often extremely difficult to examine due to the fact that they are tightly packed and contain a wide variety of cluttered and occluded objects. Because of these limitations, major airports are introducing 3D x-ray Computed Tomography (CT) baggage scanning. We investigate whether we can automate the process of detecting electric devices in these 3D images of luggage. Detecting electrical devices is of particular concern as they can be used to conceal explosives. Given the massive volume of luggage that needs to be…
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Taxonomy
TopicsAdvanced X-ray and CT Imaging · Image and Object Detection Techniques · Anomaly Detection Techniques and Applications
