English

A Comparative Study of Meter Detection Methods for Automated Infrastructure Inspection

Computer Vision and Pattern Recognition 2022-05-02 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2204.14117,
  title  = {A Comparative Study of Meter Detection Methods for Automated Infrastructure Inspection},
  author = {Yusuke Ohtsubo and Takuto Sato and Hirohiko Sagawa},
  journal= {arXiv preprint arXiv:2204.14117},
  year   = {2022}
}

Comments

2 pages, in Japanese language

R2 v1 2026-06-24T11:02:40.538Z