A Novel Crack Detection Approach for Condition Assessment of Structures

Abstract

Automated health monitoring and maintenance of civil infrastructure systems is an active yet challenging area of research. Current inspection standards require an inspector to travel to a target structure site and visually assess the structure's condition. If a region is inaccessible, binoculars must be used to detect and characterize defects. This approach is labor-intensive, yet highly qualitative. A less time-consuming and inexpensive alternative to current monitoring methods is to use a robotic system that could inspect structures more frequently, and perform autonomous damage detection. Among several possible techniques, the use of optical instrumentation (e.g., digital cameras), image processing and computer vision are promising approaches as nondestructive testing methods. The feasibility of using image processing techniques to detect deterioration in structures has been acknowledged by leading researches in the field. This study presents and evaluates the technical elements for the development of a novel crack detection methodology that is based on the use of inexpensive digital cameras. Guidelines are presented for optimizing the acquisition and processing of images, thereby enhancing the quality and reliability of the damage detection approach and allowing the capture of even the slightest, which are routinely encountered in realistic field applications where the camera-object distance and image contrast are incontrollable.