Automated object detection for muon tomography data analysis

Author:

Georgadze Anzori Sh.ORCID

Abstract

Abstract In recent years, there have been ongoing efforts to improve screening technologies to improve security and prevent terrorist threats. The most widely used technologies for scanning shipping containers are gamma and X-ray radiography, which can be harmful to operators and the environment. Muon tomography screening systems are considered as a potential tool to enhance border security and prevent terrorist threats or smuggling, especially in the context of shipping container inspections. Muon tomography uses naturally occurring cosmic ray muons to create detailed images of the inside of objects, such as shipping containers, without the need for physical intervention. Various realistic smuggling scenarios were simulated using the GEANT4 toolkit. The implemented filtering algorithms successfully reduce background noise from the surrounding cargo, enabling the detection of concealed threats and contraband. With the tools provided by the ROOT data analysis package, prohibited items can be automatically detected and localized in a cargo container.

Publisher

IOP Publishing

Reference17 articles.

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