A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases
In this study, a depth camera-based intelligence method is proposed. First, road damage images are collected and transformed into a training set. Then training, defect detection, defect extraction, and classification are performed. In addition, a YOLOv5 is used to create, train, validate, and test t...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/4992321 |
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| _version_ | 1832565719632445440 |
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| author | Hao Bai Xiangyu Hu Fei Chen Zhiyong Liao Kai Li Guangjiong Ran Fengni Wei |
| author_facet | Hao Bai Xiangyu Hu Fei Chen Zhiyong Liao Kai Li Guangjiong Ran Fengni Wei |
| author_sort | Hao Bai |
| collection | DOAJ |
| description | In this study, a depth camera-based intelligence method is proposed. First, road damage images are collected and transformed into a training set. Then training, defect detection, defect extraction, and classification are performed. In addition, a YOLOv5 is used to create, train, validate, and test the label database. The method does not require a predetermined distance between the measurement target and the sensor; can be applied to moving scenes; and is important for the detection, classification, and quantification of pavement diseases. The results show that the sensor can achieve plane fitting at investigated working distances by means of a deep learning network. In addition, two pavement examples show that the detection method can save a lot of manpower and improve the detection efficiency with certain accuracy. |
| format | Article |
| id | doaj-art-709b6b7e9e0346ee981c4d96f68e1485 |
| institution | Kabale University |
| issn | 1687-8094 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-709b6b7e9e0346ee981c4d96f68e14852025-02-03T01:06:51ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/4992321A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement DiseasesHao Bai0Xiangyu Hu1Fei Chen2Zhiyong Liao3Kai Li4Guangjiong Ran5Fengni Wei6Sichuan Expressway Construction and Development Group Co., Ltd.Department of Civil and Environmental EngineeringSichuan Intelligent High-Speed Technology Co., Ltd.Sichuan Expressway Construction and Development Group Co., Ltd.Sichuan Intelligent Highway Technology Co., Ltd.Chang’an UniversityThe Hong Kong Polytechnic UniversityIn this study, a depth camera-based intelligence method is proposed. First, road damage images are collected and transformed into a training set. Then training, defect detection, defect extraction, and classification are performed. In addition, a YOLOv5 is used to create, train, validate, and test the label database. The method does not require a predetermined distance between the measurement target and the sensor; can be applied to moving scenes; and is important for the detection, classification, and quantification of pavement diseases. The results show that the sensor can achieve plane fitting at investigated working distances by means of a deep learning network. In addition, two pavement examples show that the detection method can save a lot of manpower and improve the detection efficiency with certain accuracy.http://dx.doi.org/10.1155/2022/4992321 |
| spellingShingle | Hao Bai Xiangyu Hu Fei Chen Zhiyong Liao Kai Li Guangjiong Ran Fengni Wei A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases Advances in Civil Engineering |
| title | A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases |
| title_full | A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases |
| title_fullStr | A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases |
| title_full_unstemmed | A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases |
| title_short | A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases |
| title_sort | depth camera based intelligent method for identifying and quantifying pavement diseases |
| url | http://dx.doi.org/10.1155/2022/4992321 |
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