| Title: | OS23-1 Crack Detection in a Concrete Structure Using an Underwater Vehicle |
|---|---|
| Publication: | ICAROB2021 |
| Volume: | 26 |
| Pages: | 777-781 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2021.OS23-1 |
| Author(s): | Yuya Nishida, Naoto Sohara, Shinsuke Yasukawa, Kazuo Ishii |
| Publication Date: | January 21, 2021 |
| Keywords: | Crack detection, image processing, Underwater vehicle |
| Abstract: | In this paper, to realize efficient underwater infrastructure inspection, automatic crack detection by image processing is proposed. In first process of our method generates enhanced image based on the absorbance from the turbidity meter and removes background component, and then detects crack from the enhanced image by using decision tree learning algorithm. This paper explains the algorithm of our method and shows evaluation experiment results. |
| PDF File: | https://alife-robotics.co.jp/members2021/icarob/data/html/data/OS/OS23/OS23-1.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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