Engineer: Journal of the Institution of Engineers, Sri Lanka
Automated Crack Segmentation and Width Quantification Using Deep Learning for Structural Health Monitoring of Reinforced Concrete Structures
Accurate characterization of crack geometry is critical for assessing the durability and serviceability of Reinforced Concrete (RC) structures. Although Deep Learning (DL) has significantly improved automated crack segmentation, its effectiveness in supporting engineering measurements such as crack width remains insufficiently explored. This study proposes an integrated image-based comparative study combining semantic segmentation with quantitative crack width estimation. Four deep learning models, U-Net, Attention …