Improved Image Analysis for Evaluating Concrete Damage

Abstract

The use of images, whether in routine maintenance, or postearthquake reconnaissance, has quickly become the preferred approach to record and archive the exterior damage of existing infrastructure. Postsurvey analysis of these images, coupled with careful record keeping, provide invaluable data regarding the health of a structure. However, often significant amounts of data are obtained, especially for large structures, such as bridges. Therefore an automated procedure, which reliably and robustly reports on damage observed from these images, with minimal human intervention, is desirable. To this end, in this work, we present a statistical-based method for conducting image analysis, specifically for the purpose of evaluating concrete damage (cracks, spalling, etc.). We illustrate the derivation of the method, which is grounded in Bayesian decision theory and subsequently present results of the analysis of images with discrete cracks to illustrate its promise.