一种基于转换的适应性标记物检测和定位方法,用于使用无人机进行位移测量
Jianlin Liu1, Wujiao Dai1, Yunsheng Zhang1
1Department of Surveying Engineering & Geo-Informatics, Central South University, Changsha 410083, China.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
本研究引入了一种适应性拉顿转换方法,用于精确检测无人机 (UAV) 图像中的十字形标记物,从而提高变形监测的准确性. 新方法实现了97.2%的检测率和0.57像素的误差,优于现有技术.
科学领域:
- 地理学工程 工程地质学
- 这是一种摄影计量技术 (photogrammetry).
- 遥感 遥感 遥感 遥感
背景情况:
- 无人驾驶飞行器 (UAV) 提供灵活的变形监测,但存在影响准确度的图像质量问题.
- 现有的方法难以快速准确地检测十字形标记,这对于无人机监测至关重要.
研究的目的:
- 开发一种基于变换的适应性方法,用于在无人机图像中准确检测和定位十字形标记.
- 通过克服标记器检测的局限性来提高无人机位移测量的精度.
主要方法:
- 开发了一个自适应性拉顿转换算法,专注于优化标记信息采集半径和边缘宽度参数.
- 该方法在各种飞行高度,标记尺寸和参数设置下进行了测试.
主要成果:
- 在各种实验条件下实现了97.2%的标记物检测率.
- 在标记器检测和定位方面获得0.57像素的根平均平方误差,明显超过其他方法.
- 确定了不同无人机高度的关键检测半径和最佳参数组合.
结论:
- 拟议的自适应性转换方法显著提高了无人机图像中十字形标记器检测的准确性和可靠性.
- 这种技术为改善无人机变形监测提供了实用解决方案,特别是用于位移测量.
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