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Smart city article details

Title	An Automatic Road Crack Detection System
ID_Doc	7709
Authors	Alshami A.; Alflih R.; Almushaigh R.; Alhasson H.
Year	2022
Published	Proceedings of 2022 2nd International Conference on Computing and Information Technology, ICCIT 2022
DOI	http://dx.doi.org/10.1109/ICCIT52419.2022.9711615
Abstract	Recently, there has been attention to smart city and the increasing of labour costs, how to continuously and automatically monitor the structure with the least amount of manpower has become an important research direction. Therefore, there are tremendous robotic-based applications designed to observe, predict, or detect the changes that could happen in the civil engineering infrastructure. One of these applications is detecting road cracks. In this paper, an overview is conducted to explain the automatic crack detection systems then we present a detailed analysis about extracting the road cracks. In particular, U-Net is one type of Fully Connected Convolutional Neural Network that can be applied on various road crack datasets. Our contribution is addressing the U-Net issue with fixed sizing for input images by combining traditional image processing methods with the U-Net model with focusing on a region of interest. This research can be benefited to control the traffic speed, grantee safety on roads and regular maintain civil infrastructure. © 2022 IEEE.
Author Keywords	Detection; Edges and ridges detection; Road crack; ROI; U-Net

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