2022/04/24 by Yusuke Ohtsubo, Ohtsubo, Yusuke, Takuto Sato +3
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Object Detection Techniques #Industrial Vision Systems and Defect Detection #Infrastructure Maintenance and Monitoring #cs.CV
paper · pdf · doi:10.48550/arxiv.2204.14117
2 pages, in Japanese language
arxiv created 2022/04/24 · openalex publication_date 2022/04/24 · arxiv updated 2022/05/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In order to read meter values from a camera on an autonomous inspection robot with positional errors, it is necessary to detect meter regions from the image. In this study, we developed shape-based, texture-based, and background information-based methods as meter area detection techniques and compared their effectiveness for meters of different shapes and sizes. As a result, we confirmed that the background information-based method can detect the farthest meters regardless of the shape and number of meters, and can stably detect meters with a diameter of 40px.