Crack identification method for concrete structures considering angle of view using RGB-D camera-based sensor fusion. (March 2021)

• Record Type: Journal Article
• Authors: Kim, Hyunjun; Lee, Sahyeon; Ahn, Eunjong; Shin, Myoungsu; Sim, Sung-Han
• Is Part Of: Structural health monitoring. Volume 20:Number 2(2021)
• Page Start: 500
• Page End: 512
• Publication Date: 2021-03
• Subjects: Concrete structure -- crack identification -- digital image processing -- RGB-D information -- sensor fusion; Structural health monitoring -- Periodicals; Structural stability -- Periodicals; Strength of materials -- Periodicals; Nondestructive testing -- Periodicals; Constructions -- Stabilité -- Périodiques; Résistance des matériaux -- Périodiques; Contrôle non destructif -- Périodiques; Electronic journals; 624.17
• DOI: 10.1177/1475921720934758
• Languages: English
• ISSNs: 1475-9217

Abstract

Cracks on concrete structures are an important indicator for assessing concrete durability and structural safety. Although such cracks are typically monitored by manual visual inspection, this method has drawbacks in terms of inspection time, safety, cost-effectiveness, and measurement accuracy. An innovative alternative is digital image processing, which can be used to obtain crack information from images captured using a digital camera. However, in image-based crack detection, the crack width may vary depending on the angle of the camera with respect to the concrete surface. A skewed angle of view is often encountered, particularly when capturing images from unmanned aerial vehicles or from higher locations. This study proposes a crack identification strategy using a combination of RGB-D and high-resolution digital cameras to accurately measure cracks regardless of the angle of view. The camera system is equipped with a tailored sensor fusion algorithm for crack identification, enabling a high measurement resolution and a robust depth estimation considering the skewed angle problem. An approximate plane corresponding to the concrete surface is introduced to effectively handle the high noise in the depth measurement data of the RGB-D camera. Subsequently, the crack image captured using the high-resolution digital camera is mapped onto the obtained plane model, allowing the crack width to be determined using the three-dimensional coordinates of each crack pixel. The measurement accuracy of the proposed approach is experimentally validated on an actual concrete structure.