Effects of Turbidity and Lighting on the Performance of an Image Processing based Damage Detection Technique

Measuring the true extent of damage in a structure remains a difficult task for inspectors. For visual inspections, an accurate assessment of the damage state is often subjective in nature and prone to error, especially when an inspection is conducted in hostile surroundings or when there are challenging environmental conditions present. While incorporating some form of Non-Destructive Technique (NDT) is generally useful for the inspection process, its performance may similarly degrade in the presence of environmental conditions. It is thus of great practical importance to have a measure of the performance of an NDT for a host of varying conditions, thereby allowing the inspector to determine whether it could be successfully applied in a given situation. In this paper, a measure of the effectiveness of an NDT is probabilistically determined for various environmental conditions through the use of Receiver Operating Characteristic (ROC) curves. ROC curves offer a convenient way of characterizing and comparing the performance of an NDT under various conditions. The NDT considered in this paper is an image processing based damage detection technique which uses texture information in conjunction with Support Vector Machine (SVM) classification to identify damaged regions. The variability of this technique is evaluated for various damage forms that are subjected to two changing parameters; turbidity and lighting. There were three set levels (low, medium, high) for each parameter. The conditions that were conducive to good detection were isolated and ranked using the α-δ method as part of the ROC analysis. The technique is applied to standard dynamic range (SDR) images and high dynamic range (HDR) images in order to assess their respective sensitivities to the changing parameters.