CUED Publications database

Large Scale Column Detection for Bridge Inspection

Zhu, Z and German, S and Brilakis, I (2010) Large Scale Column Detection for Bridge Inspection. In: ASCE Construction Research Congress, 2010-5-8 to 2010-5-11, Banff, AB, United States of America pp. 459-469..

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Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div D > Construction Engineering
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 20:31
Last Modified: 02 Mar 2021 08:04
DOI: 10.1061/41109(373)64