Threat detection in X-ray security screening is critical for preventing concealed threats in airports and other high-security venue where Improvised Explosive Devices (IEDs) remain among the most persistent and dangerous threats.
The lack of a representative, and publicly available IED dataset has limited the development of machine-learning based automated threat detection systems. To address these issues, we propose an open access dataset, called IEDXray constructed for automated detection of IEDs. The dataset comprises 17,360 X-ray images captured under a strategic concealment protocol, covering scenarios ranging from isolated threats to heavily cluttered baggage environments. It includes diverse IED types—homemade explosives, batteries, and modified devices such as laptops, mobile phones, pagers, and walkie-talkies.
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Source: Springer Nature News
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