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A reference architecture for plausible Threat Image Projection (TIP) within 3D X-ray computed tomography volumes.

Wang, Q. and Megherbi, N. and Breckon, T.P. (2020) 'A reference architecture for plausible Threat Image Projection (TIP) within 3D X-ray computed tomography volumes.', Journal of X-ray science and technology., 28 (3). pp. 507-526.

Abstract

BACKGROUND: Threat Image Projection (TIP) is a technique used in X-ray security baggage screening systems that superimposes a threat object signature onto a benign X-ray baggage image in a plausible and realistic manner. It has been shown to be highly effective in evaluating the ongoing performance of human operators, improving their vigilance and performance on threat detection. OBJECTIVE: With the increasing use of 3D Computed Tomography (CT) in aviation security for both hold and cabin baggage screening a significant challenge arises in extending TIP to 3D CT volumes due to the difficulty in 3D CT volume segmentation and the proper insertion location determination. In this paper, we present an approach for 3D TIP in CT volumes targeting realistic and plausible threat object insertion within 3D CT baggage images. METHOD: The proposed approach consists of dual threat (source) and baggage (target) volume segmentation, particle swarm optimisation based insertion determination and metal artefact generation. In our experiments, real baggage data collected from airports are used to generate TIP volumes for evaluation. We also propose a TIP quality score metric to automatically estimate the quality of generated TIP volumes. RESULT: In our experiments with real baggage CT volumes and varying threat items, 90.25% of the generated TIP volumes are graded as good by human evaluation, 7% of them are of medium quality with minor flaws and 2.75% of them are bad. CONCLUSION: Qualitative evaluations on real 3D CT baggage imagery show that our approach is able to generate realistic and plausible TIP which are indiscernible from real CT volumes and the TIP quality scores are consistent with human evaluations.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.3233/XST-200654
Publisher statement:The final publication is available at IOS Press through https://doi.org/10.3233/XST-200654
Date accepted:05 April 2020
Date deposited:26 April 2020
Date of first online publication:09 June 2020
Date first made open access:26 April 2020

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