图像处理
数字图像处理
计算机科学
计算机视觉
点云
轮缘
平面(几何)
人工智能
数字图像
结构工程
图像(数学)
工程类
几何学
数学
作者
Yu-Fei Liu,Soojin Cho,Billie F. Spencer,Jian-Sheng Fan
出处
期刊:Journal of Computing in Civil Engineering
[American Society of Civil Engineers]
日期:2014-12-02
卷期号:30 (1)
被引量:141
标识
DOI:10.1061/(asce)cp.1943-5487.0000446
摘要
Traditional crack assessment methods for concrete structures are time consuming and produce subjective results. The development of a means for automated assessment employing digital image processing offers high potential for practical implementation. However, two problems in two-dimensional (2D) image processing hinder direct application for crack assessment, as follows: (1) the image used for the digital image processing has to be taken perpendicular to the surface of the concrete structure, and (2) the working distance used in retrieving the imaging model has to be measured each time. To address these problems, this paper proposes a combination of 2D image processing and three-dimensional (3D) scene reconstruction to locate the 3D position of crack edges. In the proposed algorithm, first the precise crack information is obtained from the 2D images after noise elimination and crack detection using image processing techniques. Then, 3D reconstruction is conducted employing several crack images to build the 3D scene, and the surfaces in the scene are estimated by plane fitting using the 3D point cloud. Subsequently, the crack is projected from the 2D image onto the 3D concrete surface with a crack so that the precise 3D coordinates of the crack edges are found. The final crack assessment results are given using the scaled 3D crack information. Field tests were conducted on a concrete wall including single and multiple concrete surface tests, and a concrete flange with complex crack shape, respectively. The results indicate that the proposed approach overcomes existing hurdles to offer a new tool for monitoring the health of concrete structures.
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