Enhanced detonators detection in X-ray baggage inspection by image manipulation and deep convolutional neural networks


The detection of dangerous objects in X-ray images of baggage has become important, particularly due to rising crime rates. The performance of screening devices is strongly influenced by the target visibility, image display technology, and the security officers’ knowledge.

However, visual inspection of these images is highly challenging due to the low prevalence of targets, variability in target visibility (resulting in lack of precision in object shape), overlapping objects, poor contrast that obscures image details, and the potential for causing false alarms. Furthermore, the constant and repetitive nature of the task i.e., the security officers constantly looking at screens and frequently encountering the same types of detected objects, can lead to attention fatigue and impaired judgment4.

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Source: Nature