基于图像的混凝土裂检测方法,使用中位数绝对偏差
Juan Camilo Avendaño1, John Leander1, Raid Karoumi1
1Division of Structural Engineering and Bridges, KTH Royal Institute of Technology, 10044 Stockholm, Sweden.
Sensors (Basel, Switzerland)
|May 11, 2024
概括
本研究介绍了一种适应性图像分析方法,用于检测混凝土裂. 这种新的方法可以准确地识别小到0.1毫米的裂,超过现有技术的性能.
科学领域:
- 土木工程 土木工程是指土木工程.
- 材料科学 材料科学 材料科学
- 计算机视觉 计算机视觉
背景情况:
- 精确的混凝土裂检测对于结构健康监测至关重要.
- 现有的方法经常在不同的裂宽度和图像条件下扎.
- 图像处理技术为自动化裂分析提供了潜力.
研究的目的:
- 开发和评估一种适应性值方法,用于混凝土裂的检测和量化.
- 将拟议方法的性能与Otsu和Niblack等既有技术进行比较.
- 评估该方法在检测和测量狭窄裂纹方面的能力.
主要方法:
- 使用基于中位数绝对偏差 (MAD) 的自适应值技术.
- 进行有限的预处理,然后对子图像进行动态值的确定.
- 拉普拉斯边缘检测用于裂纹边缘识别和以中心线为基础的宽度测量.
主要成果:
- 拟议的方法成功地检测出高概率 (94%) 的0.1毫米小的裂.
- 对于较宽的裂,检测概率达到100%.
- 与Otsu和Niblack方法相比,精确度,精度和F2得分都更高.
结论:
- 基于MAD的自适应值方法为混凝土裂分析提供了强大而准确的解决方案.
- 这种技术在破裂检测方面显著改进了传统的图像处理方法.
- 该方法有望加强结构健康监测和具体基础设施评估.
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