Accurate Extraction Of Cracks On The Underside Of Concrete Bridges

Crack detection is crucial for maintaining the structural health and safety of concrete bridges. Previous studies mainly focus on the detection of thick and conspicuous cracks on bridge deck using high resolution images. However, it's difficult to obtain accurate crack detection results on the underside of bridges due to the fainter and thinner appearance and lower contrast of cracks to their background. To overcome this problem, we propose a modified Beamlet Tree-based crack detection method which searches for possible edges by hierarchically constructing difference filters. The proposed method is evaluated with real crack images on the underside of bridges collected by an unmanned aerial vehicle (UAV). Compared with competitors, our proposed method achieves better performance in terms of accuracy and completeness.