Department of Science and Technology, College of Ranyah, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
Faculty of Computer Science and Information Technology, Al-Baha University, Al-Baha 65528, Saudi Arabia.
Sensors (Basel). 2023 Mar 29;23(7):3578. doi: 10.3390/s23073578.
Advances in semiconductor technology and wireless sensor networks have permitted the development of automated inspection at diverse scales (machine, human, infrastructure, environment, etc.). However, automated identification of road cracks is still in its early stages. This is largely owing to the difficulty obtaining pavement photographs and the tiny size of flaws (cracks). The existence of pavement cracks and potholes reduces the value of the infrastructure, thus the severity of the fracture must be estimated. Annually, operators in many nations must audit thousands of kilometers of road to locate this degradation. This procedure is costly, sluggish, and produces fairly subjective results. The goal of this work is to create an efficient automated system for crack identification, extraction, and 3D reconstruction. The creation of crack-free roads is critical to preventing traffic deaths and saving lives. The proposed method consists of five major stages: detection of flaws after processing the input picture with the Gaussian filter, contrast adjustment, and ultimately, threshold-based segmentation. We created a database of road cracks to assess the efficacy of our proposed method. The result obtained are commendable and outperform previous state-of-the-art studies.
半导体技术和无线传感器网络的进步使得在不同尺度上（机器、人类、基础设施、环境等）实现自动化检测成为可能。然而，道路裂缝的自动识别仍处于起步阶段。这主要是由于难以获取路面照片和缺陷（裂缝）的微小尺寸所致。路面裂缝和坑洼的存在降低了基础设施的价值，因此必须估计裂缝的严重程度。每年，许多国家的运营商都必须对数千公里的道路进行审计，以定位这种退化。这个过程既昂贵又缓慢，并且产生的结果相当主观。这项工作的目标是创建一个有效的自动系统，用于识别、提取和 3D 重建裂缝。创建无裂缝道路对于防止交通事故和拯救生命至关重要。所提出的方法包括五个主要阶段：用高斯滤波器处理输入图像后检测缺陷、对比度调整，最后是基于阈值的分割。我们创建了一个道路裂缝数据库来评估我们提出的方法的效果。得到的结果令人赞赏，优于以前的最先进研究。
