Automatic detection and dimensional measurement of concrete bridge crack based on machine vision

Tianlong Yang; Qiancheng Zhao; Xian Wang

doi:10.1117/12.2548269

16 October 2019 Automatic detection and dimensional measurement of concrete bridge crack based on machine vision

Tianlong Yang, Qiancheng Zhao, Xian Wang

Proceedings Volume 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019); 1120528 (2019) https://doi.org/10.1117/12.2548269
Event: Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 2019, Phuket, Thailand

Abstract

Structural crack is an important factor which causes failure of reinforced concrete bridges. In this work, automatic detection and dimensional measurement of concrete bridge crack are researched, for improving technical level and efficiency of concrete bridge state assessment. Images containing crack features are first recognized using information entropy characteristics of intensity clustering, for promoting efficiency and robustness of rough crack localization based on proportional segmentation. After the features are refined at sub-pixel level, their actual dimensions are accurately measured employing a cross structured light system. Experiments show that the problems such as high misjudgment, low efficiency and poor accuracy in the existing technologies are preliminarily addressed; the proposed method performs well in crack detection and measurement using concrete bridge structure images.

Citation Download Citation

Tianlong Yang, Qiancheng Zhao, and Xian Wang "Automatic detection and dimensional measurement of concrete bridge crack based on machine vision", Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 1120528 (16 October 2019); https://doi.org/10.1117/12.2548269

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KEYWORDS

Bridges

Image segmentation

Cameras

Structured light

Image processing

Machine vision

Calibration

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