基于交叉尺度重叠斑块的道路裂缝检测关注网络

IF 8.4 1区 工程技术 Q1 ENGINEERING, CIVIL
Po-Hao Chen;Jun-Wei Hsieh;Yi-Kuan Hsieh;Chuan-Wang Chang;Deng-Yuan Huang
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引用次数: 0

摘要

路面裂缝对行人和司机都构成严重威胁。传统的人工裂缝检测方法不仅速度慢,而且存在安全隐患。这一过程的自动化有可能大大提高检测效率,从而提高驾驶安全性。虽然以前的方法在道路裂缝检测中显示出希望,但它们往往忽略了多个尺度之间的相互作用,导致较小的裂缝在后期检测阶段被忽视。本文介绍了基于跨尺度重叠补丁的注意力网络(COP-Net),该网络包含两个关键组件:用于裂缝检测的尺度感知通道注意力(SCA)模块和基于补丁的跨尺度注意力(PCA)模块。这些创新能够在多个尺度上进行动态推理,从而显著改善了裂纹检测和分割。值得注意的是,我们的方法在同时检测小裂缝和大裂缝方面表现出色。为了验证我们方法的有效性,我们对三个开放数据集进行了评估:CRACK500、CFD和AEL。这些评估结果表明,COP-Net优于HED、DeepCrack、UHDN、SSGNet、MFANet、FPHBN、DeepCrack、PBNet、PAFNet、CarNet和SegFormer等11种比较方法。我们的模型在分段指标(如AIU、ODS和OIS)方面达到了新的最先进(SoTA)性能水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-Scale Overlapping Patch-Based Attention Network for Road Crack Detection
Cracks on road surfaces pose serious risks to both pedestrians and drivers. Traditional manual crack detection methods are not only slow but also pose safety risks. Automating this process has the potential to greatly enhance detection efficiency and consequently improve driving safety. Although previous methods have shown promise in road crack detection, they often neglect interactions between multiple scales, causing smaller cracks to be overlooked in later stages of detection. This paper introduces the Cross-scale Overlapping Patch-based attention Network (COP-Net), which incorporates two critical components: the Scale-aware Channel Attention (SCA) module and the Patch-based Cross-scale Attention (PCA) module for crack detection. These innovations enable dynamic inference on multiple scales, resulting in a significant improvement in crack detection and segmentation. Notably, our approach excels at detecting both small and large cracks simultaneously. To validate the effectiveness of our approach, we conducted evaluations on three open datasets: CRACK500, CFD, and AEL. These evaluation results demonstrate that COP-Net surpasses eleven comparison methods, including HED, DeepCrack, UHDN, SSGNet, MFANet, FPHBN, DeepCrack, PBNet, PAFNet, CarNet, and SegFormer. Our model achieves new State-of-The-Art (SoTA) performance levels in terms of segmentation metrics such as AIU, ODS, and OIS.
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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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