Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach
文献类型：期刊论文
| 作者 | Lili Fan; Shen Li; Ying Li ; Bai Li; Dongpu Cao; Fei-Yue Wang
|
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2023 |
| 卷号 | 10期号:7页码:1593-1607 |
| 关键词 | Automatic pavement crack detection data augmentation compensation deep learning residual feature augmentation shadow removal shadow-crack dataset |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2023.123447 |
| 英文摘要 | Automatic pavement crack detection is a critical task for maintaining the pavement stability and driving safety. The task is challenging because the shadows on the pavement may have similar intensity with the crack, which interfere with the crack detection performance. Till to the present, there still lacks efficient algorithm models and training datasets to deal with the interference brought by the shadows. To fill in the gap, we made several contributions as follows. First, we proposed a new pavement shadow and crack dataset, which contains a variety of shadow and pavement pixel size combinations. It also covers all common cracks (linear cracks and network cracks), placing higher demands on crack detection methods. Second, we designed a two-step shadow-removal-oriented crack detection approach: SROCD, which improves the performance of the algorithm by first removing the shadow and then detecting it. In addition to shadows, the method can cope with other noise disturbances. Third, we explored the mechanism of how shadows affect crack detection. Based on this mechanism, we propose a data augmentation method based on the difference in brightness values, which can adapt to brightness changes caused by seasonal and weather changes. Finally, we introduced a residual feature augmentation algorithm to detect small cracks that can predict sudden disasters, and the algorithm improves the performance of the model overall. We compare our method with the state-of-the-art methods on existing pavement crack datasets and the shadow-crack dataset, and the experimental results demonstrate the superiority of our method. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/51996]  |
| 专题 | 自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica |
| 推荐引用方式 GB/T 7714 | Lili Fan,Shen Li,Ying Li,et al. Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(7):1593-1607. |
| APA | Lili Fan,Shen Li,Ying Li,Bai Li,Dongpu Cao,&Fei-Yue Wang.(2023).Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach.IEEE/CAA Journal of Automatica Sinica,10(7),1593-1607. |
| MLA | Lili Fan,et al."Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach".IEEE/CAA Journal of Automatica Sinica 10.7(2023):1593-1607. |
入库方式： OAI收割
来源：自动化研究所
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