EPJ Web Conf.
Volume 225, 2020ANIMMA 2019 – Advancements in Nuclear Instrumentation Measurement Methods and their Applications
|Number of page(s)||6|
|Section||Safeguards, Homeland Security|
|Published online||20 January 2020|
Image texture analysis and colorimetry for the classification of uranium ore concentrate powders
European Commission, Joint Research Centre (JRC)
Mara Marchetti is with the European Commission, Joint Research Centre (JRC), Ispra, Italy e-mail: firstname.lastname@example.org
Klaus Mayer, Maria Wallenius, Antonio Bulgheroni, Thierry Wiss, Klaus Lützenkirchen and Lorenzo Fongaro are with the European Commission, Joint Research Centre (JRC), Karlsruhe, Germany
Published online: 20 January 2020
In the context of nuclear security, uranium ore concentrates (UOCs) play an important role: they are traded in large quantities and this makes their use “out of regulatory control” a possible scenario.
Once an incident of illicit trafficking o f n uclear m aterial is detected, an understanding of its origin and production process is required; this implies the necessity to use analytical techniques able to measure characteristic parameters (e.g. physical, chemical, isotopic characteristics of the nuclear materials) which are referred to, in the field o f t he n uclear f orensics, a s signatures.
The present study investigates the potential of image texture analysis (i.e. the angle measure technique), combined with the spectrophotometric determination of colours for the evaluation of the origin of several UOCs. The use of different multivariate statistical techniques allows the categorization of about 80 different samples into a few groups of UOCs powders, which makes this approach a promising method complementing the already established methods in nuclear forensics.
Key words: Nuclear forensic science / Image texture analysis / spectrophotometry / PCA / SVM / AMT
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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