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 visual monitoring methods is to use a system that could inspect structures remotely and also more frequently. This article 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 this article to demonstrate the capabilities, as well as the limitations, of the proposed vision-based inspection procedure.