Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing
Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and of...
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MDPI AG
2017-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/17/9/2052 |
| _version_ | 1828272611905241088 |
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| author | Hyunjun Kim Junhwa Lee Eunjong Ahn Soojin Cho Myoungsu Shin Sung-Han Sim |
| author_facet | Hyunjun Kim Junhwa Lee Eunjong Ahn Soojin Cho Myoungsu Shin Sung-Han Sim |
| author_sort | Hyunjun Kim |
| collection | DOAJ |
| description | Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%. |
| first_indexed | 2024-04-13T06:09:20Z |
| format | Article |
| id | doaj.art-e92112f307f74bc4a8c00eacfef1c33b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:09:20Z |
| publishDate | 2017-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e92112f307f74bc4a8c00eacfef1c33b2022-12-22T02:59:07ZengMDPI AGSensors1424-82202017-09-01179205210.3390/s17092052s17092052Concrete Crack Identification Using a UAV Incorporating Hybrid Image ProcessingHyunjun Kim0Junhwa Lee1Eunjong Ahn2Soojin Cho3Myoungsu Shin4Sung-Han Sim5School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, KoreaSchool of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, KoreaSchool of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, KoreaDepartment of Civil Engineering, University of Seoul, Seoul 02504, KoreaSchool of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, KoreaSchool of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, KoreaCrack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.https://www.mdpi.com/1424-8220/17/9/2052concrete structurecrack identificationdigital image processingstructural health monitoringunmanned aerial vehicle |
| spellingShingle | Hyunjun Kim Junhwa Lee Eunjong Ahn Soojin Cho Myoungsu Shin Sung-Han Sim Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing Sensors concrete structure crack identification digital image processing structural health monitoring unmanned aerial vehicle |
| title | Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing |
| title_full | Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing |
| title_fullStr | Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing |
| title_full_unstemmed | Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing |
| title_short | Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing |
| title_sort | concrete crack identification using a uav incorporating hybrid image processing |
| topic | concrete structure crack identification digital image processing structural health monitoring unmanned aerial vehicle |
| url | https://www.mdpi.com/1424-8220/17/9/2052 |
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