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Authors: Yuma Nishikawa ; Fumihiko Sakaue and Jun Sato

Affiliation: Nagoya Institute of Technology, Japan

Keyword(s): Anomaly Inspection, Textile Product Inspection, Illumination Optimization.

Abstract: In this study, we propose a method to simultaneously learn and optimize the illumination conditions suitable for anomaly inspection and a neural network for anomaly inspection in textile product anomaly inspection. In the inspection of abnormalities in industrial products such as textile products, it is necessary to optimize the imaging environment including the lighting environment, but this process is mostly done manually by trial and error. In this study, we show that highly accurate inspection of abnormalities can be achieved by using a display whose light source position and brightness can be easily changed, and by presenting a proof pattern suitable for abnormalities on the display. Furthermore, we show how to simultaneously optimize the neural network and illumination conditions used for such anomaly inspection. We also show that the proposed method can appropriately detect anomalies using images actually taken.

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Paper citation in several formats:
Nishikawa, Y., Sakaue, F. and Sato, J. (2025). Simultaneous Optimization of Abnormality Discriminator and Illumination Conditions for Image Inspection of Textile Products. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3; ISSN 2184-4321, SciTePress, pages 755-760. DOI: 10.5220/0013322300003912

@conference{visapp25,
author={Yuma Nishikawa and Fumihiko Sakaue and Jun Sato},
title={Simultaneous Optimization of Abnormality Discriminator and Illumination Conditions for Image Inspection of Textile Products},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={755-760},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013322300003912},
isbn={978-989-758-728-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Simultaneous Optimization of Abnormality Discriminator and Illumination Conditions for Image Inspection of Textile Products
SN - 978-989-758-728-3
IS - 2184-4321
AU - Nishikawa, Y.
AU - Sakaue, F.
AU - Sato, J.
PY - 2025
SP - 755
EP - 760
DO - 10.5220/0013322300003912
PB - SciTePress

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