BARNet: Boundary Aware Refinement Network for Crack Detection

• Published in: IEEE transactions on intelligent transportation systems Vol. 23; no. 7; pp. 7343 - 7358
• Main Authors: Guo, Jing-Ming, Markoni, Herleeyandi, Lee, Jiann-Der
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Computer vision; Convolution; Deep learning; edge adaptation layer; Edge detection; Feature extraction; Image edge detection; refinement layer; Roads; Roads & highways; spatial and channel analyzer; supervision; Support vector machines; Surface cracks

Road crack is one of the prominent problems that can frequently occur in highways and main roads. The manual road crack evaluation is laborious, time-consuming, inaccurate, and it has several implementation issues. Conversely, the computer vision-based solution is very challenging due to the complex...