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Automatic detection and dimensional measurement of concrete bridge crack based on machine vision
Author(s): Tianlong Yang; Qiancheng Zhao; Xian Wang
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Paper 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.

Paper Details

Date Published: 16 October 2019
PDF: 5 pages
Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 1120528 (16 October 2019); doi: 10.1117/12.2548269
Show Author Affiliations
Tianlong Yang, Hunan Univ. of Science and Technology (China)
Qiancheng Zhao, Hunan Univ. of Science and Technology (China)
Xian Wang, Hunan Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11205:
Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019)
Anand Asundi; Motoharu Fujigaki; Huimin Xie; Qican Zhang; Song Zhang; Jianguo Zhu; Qian Kemao, Editor(s)

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