Multi-image stitching and scene reconstruction for evaluating defect evolution in structures

Abstract

It is well-recognized that civil infrastructure monitoring approaches that rely on visual approaches will continue to be an important methodology for condition assessment of such systems. Current inspection standards for structures such as bridges require an inspector to travel to a target structure site and visually assess the structure's condition. A less time-consuming and inexpensive alternative to current vision-based monitoring methods is to use a system that could inspect structures remotely and also more frequently.This paper presents and evaluates the underlying technical elements for the development of an integrated inspection software tool that is based on the use of inexpensive digital cameras. For this purpose, digital cameras are appropriately mounted on a structure (e.g., a bridge) and can zoom or rotate in three directions (similar to traffic cameras). They are remotely controlled by an inspector, which allows the visual assessment of the structure's condition by looking at images captured by the cameras. By not having to travel to the structure's site, other issues related to safety considerations and traffic detouring are consequently bypassed. The proposed system gives an inspector the ability to compare the current (visual) situation of a structure with its former condition. If an inspector notices a defect in the current view, he/she can request a reconstruction of the same view using images that were previously captured and automatically stored in a database. Furthermore, by generating databases that consist of periodically captured images of a structure, the proposed system allows an inspector to evaluate the evolution of changes by simultaneously comparing the structure's condition at different time periods. The essential components of the proposed virtual image reconstruction system are: keypoint detection, keypoint matching, image selection, outlier exclusion, bundle adjustment, composition, and cropping. Several illustrative examples are presented in the paper to demonstrate the capabilities, as well as the limitations, of the proposed vision-based inspection procedure.

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

“…The reconstructed 3D points are reprojected into images for accurate cylindrical surface estimation. Jahanshahi et al [76] create stitched images of structural systems from a specialized camera that can tilt and pan. The method detects missing parts, such as bolts, when comparing images taken at different times for the purpose of structural health monitoring (SHM).…”

Corrigendum to “A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure” [Advanced Engineering Informatics 29(2) (2015) 196–210]

“…[1, p. 36] for the purpose of structural health monitoring (SHM). Chaiyasarn [1] adds that in [13] ''the method applies a machine-vision algorithm to perform image registration to rectify images so that they are in the same coordinate frame" [1, p. 36].…”

“…The reconstructed 3D points are reprojected into images for accurate cylindrical surface estimation. According to Chaiyasarn [1], Jahanshahi et al [13] ''create stitched images of structural systems from a specialized camera that can tilt and pan. The method detects missing parts such as bolts when comparing images taken at different times [.…”

Can technology improve routine visual bridge inspections?

“…Other work has looked at the development of robotic inspection systems, which climb over the structure and collect data from close to the surface (Kim et al, 2005;Murphy and Sitti, 2007). Other, possibly simpler, approaches have considered the use of tripod-mounted cameras (Sites, 2010), or CCTV type cameras mounted permanently in place on the structure (Jahanshahi et al, 2011).…”

“…These cameras cannot move around the structure, but can be panned, tilted and zoomed into features on the bridge, either following a predetermined path, or being 'driven' remotely by an inspector. Jahanshahi et al (2011) have proposed a system that enables an inspector to watch the camera output while controlling the camera over the internet. If a feature of interest is seen, an image can be recorded and stored for later analysis, including comparison against images recorded during previous inspections.…”