Learning-based Material Classification in X-ray Security Images

Benedykciuk Emil, Denkowski Marcin, Dmitruk Krzysztof

Abstract

Although a large number of papers have been published on material classification in the X-ray images, relatively few of them study X-ray security raw images as regards of material classification. This paper takes into consideration the task of materials classification into four main types of organics and metals in images obtained from Dual-Energy X-ray (DEXA) security scanner. We adopt well-known methods of machine learning and conduct experiments to examine the effects of various combinations of data and algorithms for generalization of the material classification problem. The methods giving the best results (Random Forests and Support Vector Machine) were used to predict the materials at every pixel in the testing image. The results motivate a novel segmentation scheme based on the multi-scale patch classification. This paper also introduces a new, open dataset of X-ray images (MDD) of various materials. The database contains over one million samples, labelled and stored in its raw, original 16-bit depth form.

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Paper Citation


in Harvard Style

Emil B., Marcin D. and Krzysztof D. (2020). Learning-based Material Classification in X-ray Security Images.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-402-2, pages 284-291. DOI: 10.5220/0008951702840291


in Bibtex Style

@conference{visapp20,
author={Benedykciuk Emil and Denkowski Marcin and Dmitruk Krzysztof},
title={Learning-based Material Classification in X-ray Security Images},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2020},
pages={284-291},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008951702840291},
isbn={978-989-758-402-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Learning-based Material Classification in X-ray Security Images
SN - 978-989-758-402-2
AU - Emil B.
AU - Marcin D.
AU - Krzysztof D.
PY - 2020
SP - 284
EP - 291
DO - 10.5220/0008951702840291