Anomalous Water Dataset Captured by Hyperspectral Cameras

Youta Noboru, Yuko Ozasa

2025

Abstract

This paper proposes a hyperspectral dataset designed for detecting anomalies in water caused by the mixing of colorless and transparent anomalous liquids. Detecting such anomalous substances, particularly when they are transparent, is crucial for public health and environmental safety, as conventional methods often inadequate. Hyperspectral imaging captures subtle spectral differences, enabling the identification of materials that are visually indistinguishable. The dataset aims to support the development of unsupervised learning models that can detect anomalous substances in water using only a spectral data. We have made this dataset publicly available (https://github.com/033labcodes/visapp25\ Anomalous-Water-Dataset) to facilitate further research in this area.

Paper Citation

in Harvard Style

Noboru Y. and Ozasa Y. (2025). Anomalous Water Dataset Captured by Hyperspectral Cameras. 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, SciTePress, pages 442-449. DOI: 10.5220/0013163800003912

in Bibtex Style

@conference{visapp25,
author={Youta Noboru and Yuko Ozasa},
title={Anomalous Water Dataset Captured by Hyperspectral Cameras},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={442-449},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013163800003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Anomalous Water Dataset Captured by Hyperspectral Cameras
SN - 978-989-758-728-3
AU - Noboru Y.
AU - Ozasa Y.
PY - 2025
SP - 442
EP - 449
DO - 10.5220/0013163800003912
PB - SciTePress