路面地下目标探地雷达图像多视角语义分割

IF 8.4 1区 工程技术 Q1 ENGINEERING, CIVIL
Sibo Huang;Guijie Zhu;Jiaming Tang;Weixiong Li;Zhun Fan
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引用次数: 0

摘要

有效的基础设施健康监测在交通网络物理系统中至关重要,其中准确的道路健康检测对于确保道路安全和智能交通系统的稳定性至关重要。为了解决使用三维探地雷达(GPR)数据识别路面地下物体的挑战,我们提出了一种集成b扫描和c扫描图像的多视角级联识别方法。该方法建立在轻量级的双流语义分割模型AttnGPRNet上,该模型通过注意机制改进特征提取,增强地下物体识别。首先,该模型对b扫描图像进行分割,识别潜在的目标区域,然后在初步结果的基础上对3l - c扫描图像进行更精确的分割。此外,我们利用超过100公里的城市道路的3D GPR扫描构建了一个多视图数据集,并通过实验评估了所提出方法的有效性。实验结果表明,我们的模型优于现有的先进方法,在b扫描和3l - c扫描上的mIoU分别为78.80%和83.96%,F1分数分别为87.65%和91.07%。并将该方法应用于小宁道路GPR图像智能识别系统中,通过现场钻探验证,证明了该方法在道路健康监测中的应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Perspective Semantic Segmentation of Ground Penetrating Radar Images for Pavement Subsurface Objects
Effective infrastructure health monitoring is crucial within transportation cyber-physical systems, where accurate road health detection is vital for ensuring road safety and the stability of intelligent transportation systems. To address the challenges of identifying pavement subsurface objects using 3D ground penetrating radar (GPR) data, we propose a multi-perspective cascading recognition method that integrates B-scan and C-scan images. This method is built on a lightweight dual-stream semantic segmentation model called AttnGPRNet, developed in this work to improve feature extraction through attention mechanisms and enhance subsurface object recognition. Initially, the model segments B-scan images to identify potential target regions, followed by more precise segmentation of 3L-C-scan images based on preliminary results. Additionally, we constructed a multi-view dataset using 3D GPR scans from over 100 kilometers of urban roads and evaluated the effectiveness of the proposed method through experiments. Experimental results show that our model outperforms existing advanced methods, achieving mIoU of 78.80% and 83.96% on B-scan and 3L-C-scan, and F1 scores of 87.65% and 91.07%, respectively. Moreover, the method has been deployed in Xiaoning Road GPR image intelligent recognition system and verified through on-site drilling, demonstrating its practical potential for road health monitoring.
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来源期刊
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems 工程技术-工程:电子与电气
CiteScore
14.80
自引率
12.90%
发文量
1872
审稿时长
7.5 months
期刊介绍: The theoretical, experimental and operational aspects of electrical and electronics engineering and information technologies as applied to Intelligent Transportation Systems (ITS). Intelligent Transportation Systems are defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems of all kinds. The scope of this interdisciplinary activity includes the promotion, consolidation and coordination of ITS technical activities among IEEE entities, and providing a focus for cooperative activities, both internally and externally.
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