A review of automated image understanding within 3D baggage computed tomography security screening

Subtitle:

Article type: Research Article

Authors: Mouton, Andre^{a; *} | Breckon, Toby P.^b

Affiliations: [a] School of Engineering, Cranfield University, Bedfordshire, UK | [b] School of Engineering and Computing Sciences, Durham University, Durham, UK

Correspondence: [*] Corresponding author: Andre Mouton, School of Engineering, Cranfield University, Bedfordshire, UK. E-mail:amouton@bath.ac.uk

Abstract: Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.

Keywords: Baggage screening, automated image understanding, dual-energy computed tomography, computer vision

DOI: 10.3233/XST-150508

Journal: Journal of X-Ray Science and Technology, vol. 23, no. 5, pp. 531-555, 2015