| description abstract | Cracking is one of the major distresses impacting pavement quality, serviceability, and lifespan. Thus, accurate, precise, and complete cracking detection is important in the maintenance, performance evaluation, structure, and material design of pavements. Given that the results of pavement crack image recognition tend to contain noises and intermittent crack segments, an automatic crack detection algorithm based on the connectivity checking of pixels and crack block levels was proposed. First, a pavement image was enhanced on the basis of a self-adaptive grayscale stretch. The image was then segmented into background and foreground (potential cracks) on the basis of self-adaptive OTSU segmentation and 8-direction Sobel gradients. The potential crack image was denoised through connectivity checking. Finally, | |
