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Authors: Marcin Kopaczka ; Marco Saggiomo ; Moritz Güttler ; Thomas Gries and Dorit Merhof

Affiliation: RWTH Aachen University, Germany

Keyword(s): Automated Visual Inspection, Industrial Image Processing, Air-jet Weaving Machine.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Image Understanding ; Pattern Recognition

Abstract: In this paper, we present a novel approach for the fully automated detection of faulty weft threads on air-jet weaving machines using computer vision. The proposed system consists of a camera array for image acquisition and a classification pipeline in which we use different image processing and machine learning methods to allow precise localization and reliable classification of defects. The camera system is introduced and its advantages over other approaches are discussed. Subsequently, the processing steps are motivated and described in detail, followed by an in-depth analysis of the impact of different system parameters to allow chosing optimal algorithm combinations for the problem of faulty weft yarn detection. To analyze the capabilities of our solution, system performance is thoroughly evaluated under realistic production settings, showing excellent detection rates.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kopaczka, M. ; Saggiomo, M. ; Güttler, M. ; Gries, T. and Merhof, D. (2018). Fully Automatic Faulty Weft Thread Detection using a Camera System and Feature-based Pattern Recognition. In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-276-9; ISSN 2184-4313, SciTePress, pages 124-132. DOI: 10.5220/0006591301240132

@conference{icpram18,
author={Marcin Kopaczka and Marco Saggiomo and Moritz Güttler and Thomas Gries and Dorit Merhof},
title={Fully Automatic Faulty Weft Thread Detection using a Camera System and Feature-based Pattern Recognition},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2018},
pages={124-132},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006591301240132},
isbn={978-989-758-276-9},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Fully Automatic Faulty Weft Thread Detection using a Camera System and Feature-based Pattern Recognition
SN - 978-989-758-276-9
IS - 2184-4313
AU - Kopaczka, M.
AU - Saggiomo, M.
AU - Güttler, M.
AU - Gries, T.
AU - Merhof, D.
PY - 2018
SP - 124
EP - 132
DO - 10.5220/0006591301240132
PB - SciTePress

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