Abstract
In the last decades, baggage inspection based on X-ray imaging has been established to protect environments in which access control is of vital significance. In several public entrances, like airports, government buildings, stadiums and large event venues, security checks are carried out on all baggage to detect suspicious objects (e.g., handguns and explosives). Although improvements in X-ray technology and computer vision have made many X-ray detection tasks that were previously unfeasible a reality, the progress that has been made in automated baggage inspection is very limited compared to what is needed. For this reason, X-ray screening systems are usually being manipulated by human inspectors. Research and development experts who focus on X-ray testing are moving towards new approaches that can be used to aid human operators. This paper reports the state of the art in baggage inspection identifying three research fields that have been used to deal with this problem: i) X-ray energies, because there is enough research evidence to show that multi-energy X-ray testing must be used when the material characterization is required; ii) X-ray multi-views, because they can be an effective option for examining complex objects where the uncertainty of only one view can lead to misinterpretation; and iii) X-ray computer vision algorithms, because there are a plethora of computer vision approaches that can address many 3D object recognition problems. Besides, this paper presents useful public datasets that can be used for training and testing, and also summarizes the reported experimental results in this field. Finally, this paper addresses the general limitations and show new avenues for future research.
Highlights
In the last decades, baggage inspection based on X-ray testing has been established to protect environments in which access control is of vital significance
In R & D the attempt is made to design new approaches that can support the operation of human inspectors
In the field of baggage inspection, three main factors can have an impact on detection: i) the type of X-ray image, which depends on the X-ray energies used in the image acquisition process; ii) the point of view, that means the occlusion, which depends on whether or not other objects are superimposed over the target object, and the pose, which is related to the rotation of the object; and iii) image complexity, which depends on the number of objects present and how they are placed in the bag
Summary
Baggage inspection based on X-ray testing has been established to protect environments in which access control is of vital significance. In the field of baggage inspection, three main factors can have an impact on detection: i) the type of X-ray image, which depends on the X-ray energies used in the image acquisition process; ii) the point of view, that means the occlusion, which depends on whether or not other objects are superimposed over the target object, and the pose, which is related to the rotation of the object; and iii) image complexity, which depends on the number of objects present and how they are placed in the bag These factors have been addressed using a 3X-strategy: it is clear that certain objects of interest require more than one X-ray energy (e.g., organic materials), more than one view (e.g., razor blades) and more than a simple algorithm (e.g., handguns).
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