-
- WANG Chao
- Department of Artificial Intelligence, Kyushu Institute of Technology
-
- OKUYAMA Michihiko
- Department of Artificial Intelligence, Kyushu Institute of Technology
-
- MATSUOKA Ryo
- Faculty of Environmental Engineering, The University of Kitakyushu
-
- OKABE Takahiro
- Department of Artificial Intelligence, Kyushu Institute of Technology
抄録
<p>Water detection is important for machine vision applications such as visual inspection and robot motion planning. In this paper, we propose an approach to per-pixel water detection on unknown surfaces with a hyperspectral image. Our proposed method is based on the water spectral characteristics: water is transparent for visible light but translucent/opaque for near-infrared light and therefore the apparent near-infrared spectral reflectance of a surface is smaller than the original one when water is present on it. Specifically, we use a linear combination of a small number of basis vector to approximate the spectral reflectance and estimate the original near-infrared reflectance from the visible reflectance (which does not depend on the presence or absence of water) to detect water. We conducted a number of experiments using real images and show that our method, which estimates near-infrared spectral reflectance based on the visible spectral reflectance, has better performance than existing techniques.</p>
収録刊行物
-
- IEICE Transactions on Information and Systems
-
IEICE Transactions on Information and Systems E104.D (10), 1555-1562, 2021-10-01
一般社団法人 電子情報通信学会
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390571039716214912
-
- NII論文ID
- 130008095593
-
- ISSN
- 17451361
- 09168532
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- Crossref
- CiNii Articles
- KAKEN
-
- 抄録ライセンスフラグ
- 使用不可