对高枢纽智能检查视觉感知方法的全面调查
Zhangjun Peng1,2, Li Li2,3, Daoguang Liu1,2
1School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China.
Sensors (Basel, Switzerland)
|August 29, 2024
概括
使用视觉感知技术 (如无人机和人工智能) 的智能检查提高了高的安全性. 本次审查涵盖了图像增强,缺陷检测和损害量化方法,以实现更高效,更准确的水监测.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 高安全检查对于运营完整性至关重要.
- 传统的手工检查效率低,劳动密集型,容易出现主观错误.
研究的目的:
- 审查用于智能高检查的视觉感知技术的最新进展.
- 分类和分析图像增强,缺陷检测和损坏量化方法.
主要方法:
- 图像增强技术的分类 (直方体平衡,Retinex,深度学习).
- 审查缺陷和障碍感知方法 (传统的图像处理,机器学习).
- 基于视觉感知的损害量化方法的分析.
主要成果:
- 详细阐述代表方法及其在每个类别内的特点.
- 在缺陷和障碍感知方面的主要成就的系统列举.
- 对损害量化关键技术和特征的分析.
结论:
- 使用视觉感知进行智能检查是高安全的可行和必要的进步.
- 目前的研究表明,在图像增强和缺陷检测方面取得了重大进展.
- 未来的研究应该解决应用这些技术用于全面智能安全检查的挑战.
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