Detection of large-scale concrete columns for automated bridge inspection
Detection of large-scale concrete columns for automated bridge inspection
复制标题
用于自动化桥梁检测的大型混凝土柱检测
DOI：
10.1016/j.autcon.2010.07.016
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发表时间：
2010
影响因子：
10.3
通讯作者：
I. Brilakis
中科院分区：
文献类型：
--
作者：
Zhenhua Zhu;S. German;I. Brilakis
美国有60多万座桥梁，并不是所有的桥梁都能在规定的时间内进行检查和维护。这是因为人工检查桥梁是一项既耗时又昂贵的任务，一些州交通部(DOT)负担不起必要的成本和人力。本文提出了一种能够检测大型桥梁混凝土柱的新方法，以期最终建立一个自动化的桥梁状态评估系统。该方法利用图像拼接技术(特征检测和匹配、图像仿射变换和混合)将包含一列不同片段的图像组合成一幅图像。然后，通过定位桥柱的边界并对拼接图像中每个边界内的材料进行分类来检测桥柱。对114根混凝土桥柱的初步检测结果表明，该方法能够正确检测出其中89.7%的元素，从而验证了本研究应用的可行性。
There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.