Tracking of Defects in Reinforced Concrete Bridges Using Digital Images

Abstract

This paper proposes a novel approach for the periodic detection of defects in concrete bridges based on a set of dimensionless metrics pertinent to fractal analysis of digital images. Visual inspection and image subtraction methods are generally used for the periodic comparison of structural conditions. However, such approaches, such as visual inspections, have been identified with several limitations, but they are time consuming processes and decisions are influenced by individual experiences. Likewise, image subtraction method requires image registration, which is a difficult process in achieving precise image registration for reliable outputs. This research uses fractal analysis of digital images to track surface defects by estimating their fractal dimensions. The results of the fractal analysis of concrete beams are compared with the results of spectral analysis which requires images to be translated from spatial domain to frequency domain. The proposed method successfully generates unique metrics necessary for change quantification which overcomes the limitation of the existing approaches.