Change Detection on Pipe Outer Surface via Reference Image Extraction from Past Video Using Feature Points
-
- Shimizu Susumu
- The University of Tokyo
-
- Igaue Takuya
- The University of Tokyo
-
- Louhi Kasahara Jun Younes
- The University of Tokyo
-
- Yamato Naoya
- ENEOS Corporation
-
- Kasahara Seiji
- ENEOS Corporation
-
- Ito Hiroyuki
- ENEOS Corporation
-
- Daito Taizo
- ENEOS Corporation
-
- Tamura Sunao
- ENEOS Corporation
-
- Sasamura Akinobu
- ENEOS Corporation
-
- Kato Toshiya
- ENEOS Corporation
-
- Kanda Shinji
- The University of Tokyo
-
- Nagatani Keiji
- The University of Tokyo
-
- Asama Hajime
- The University of Tokyo
-
- An Qi
- The University of Tokyo
-
- Yamashita Atsushi
- The University of Tokyo
Bibliographic Information
- Other Title
-
- 特徴量を用いた過去動画からの参照画像抽出による配管外面の変化検知
Description
<p>In this study, we propose a method for detecting changes on the outer surface of pipes using inspection videos captured by a patrol inspection robot. In patrol inspections, it is important to detect changes on the outer surface of pipes by comparing them with their past normal state. Therefore, comparing the videos before and after the changes is crucial for change detection. In the proposed method, we extracted comparison image pairs using image features from videos captured by a camera on a mobile robot and performed change detection using deep learning. This method achieved a detection accuracy of 93.9% for changes in the inspection videos.</p>
Journal
-
- Proceedings of JSPE Semestrial Meeting
-
Proceedings of JSPE Semestrial Meeting 2023A (0), 589-590, 2023-08-31
The Japan Society for Precision Engineering
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1390580793828773888
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
-
- Abstract License Flag
- Disallowed