论文标题
对自动基础设施检查的仪表检测方法的比较研究
A Comparative Study of Meter Detection Methods for Automated Infrastructure Inspection
论文作者
论文摘要
为了从具有位置错误的自主检查机器人上读取仪表值，必须从图像中检测仪表区域。在这项研究中，我们开发了基于形状的，基于纹理的，基于纹理的方法和基于背景信息的方法作为仪表区域检测技术，并比较了它们对不同形状和尺寸米的有效性。结果，我们确认基于背景信息的方法可以检测到最远的仪表，而不论其形状和米数如何，并且可以稳定地检测到直径为40px的仪表。
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.
