  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 is a technique that
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. In this paper, we describe the algorithms that allow automatic
detection of illegal dangerous items hidden inside legal cargo in shipping
containers. We used the Point of Closest Approach (PoCA) reconstruction
algorithm to reconstruct the 3D image of the shipping container and applied the
nearest neighbor filtering method to separate and differentiate the filament
materials from the complex structure of the surrounding common materials. The
use of these methods makes it possible to identify implicit information in the
data and visualize the contents of transport containers with precise
localization of threats or contraband materials.
