Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination
Visual identification of reinforced concrete structure defects is vital to ensuring structural longevity and resilience. This paper explores the use of selective reflection imaging for concrete surface corrosion and exposed reinforcement detection and measurement. Selective reflection occurs when ce...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2025/03/matecconf_cs2025_03006.pdf |
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| _version_ | 1849431055566635008 |
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| author | Dow Hamish Darby Andrew Perry Marcus Zhang Feng |
| author_facet | Dow Hamish Darby Andrew Perry Marcus Zhang Feng |
| author_sort | Dow Hamish |
| collection | DOAJ |
| description | Visual identification of reinforced concrete structure defects is vital to ensuring structural longevity and resilience. This paper explores the use of selective reflection imaging for concrete surface corrosion and exposed reinforcement detection and measurement. Selective reflection occurs when certain image colours are reflected more strongly than others by a surface. This effect can enhance colour contrast, making certain objects in a captured image appear darker. By imaging concrete surfaces using a blue lighting source, the contrast of red-coloured corrosion and exposed reinforcement is enhanced, particularly in greyscale images used by many defect detection algorithms. An inspection algorithm is proposed to segment these features using blue light images and Otsu thresholding, enabling accurate measurement of corrosion surface area. On laboratory slab samples, the algorithm obtained Intersection over Union (IoU) scores of over 84 % when compared to human-defined ground truths. Additionally, the algorithm’s corrosion surface area measurements produced a maximum relative error of negative 8 %. These findings demonstrate how colour-controlled illumination can enhance visual inspections, leading to more efficient monitoring and improved durability of reinforced concrete structures. |
| format | Article |
| id | doaj-art-ac80e9cd6d004b0ca8b06094b77969cf |
| institution | Kabale University |
| issn | 2261-236X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj-art-ac80e9cd6d004b0ca8b06094b77969cf2025-08-20T03:27:46ZengEDP SciencesMATEC Web of Conferences2261-236X2025-01-014090300610.1051/matecconf/202540903006matecconf_cs2025_03006Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illuminationDow Hamish0Darby Andrew1Perry Marcus2Zhang Feng3Department of Civil and Environmental Engineering, University of StrathclydeDepartment of Civil and Environmental Engineering, University of StrathclydeDepartment of Civil and Environmental Engineering, University of StrathclydeDepartment of Civil and Environmental Engineering, University of StrathclydeVisual identification of reinforced concrete structure defects is vital to ensuring structural longevity and resilience. This paper explores the use of selective reflection imaging for concrete surface corrosion and exposed reinforcement detection and measurement. Selective reflection occurs when certain image colours are reflected more strongly than others by a surface. This effect can enhance colour contrast, making certain objects in a captured image appear darker. By imaging concrete surfaces using a blue lighting source, the contrast of red-coloured corrosion and exposed reinforcement is enhanced, particularly in greyscale images used by many defect detection algorithms. An inspection algorithm is proposed to segment these features using blue light images and Otsu thresholding, enabling accurate measurement of corrosion surface area. On laboratory slab samples, the algorithm obtained Intersection over Union (IoU) scores of over 84 % when compared to human-defined ground truths. Additionally, the algorithm’s corrosion surface area measurements produced a maximum relative error of negative 8 %. These findings demonstrate how colour-controlled illumination can enhance visual inspections, leading to more efficient monitoring and improved durability of reinforced concrete structures.https://www.matec-conferences.org/articles/matecconf/pdf/2025/03/matecconf_cs2025_03006.pdf |
| spellingShingle | Dow Hamish Darby Andrew Perry Marcus Zhang Feng Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination MATEC Web of Conferences |
| title | Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination |
| title_full | Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination |
| title_fullStr | Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination |
| title_full_unstemmed | Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination |
| title_short | Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination |
| title_sort | automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2025/03/matecconf_cs2025_03006.pdf |
| work_keys_str_mv | AT dowhamish automatedconcreteexposedreinforcementandcorrosiondetectionandmeasurementusingcolouredillumination AT darbyandrew automatedconcreteexposedreinforcementandcorrosiondetectionandmeasurementusingcolouredillumination AT perrymarcus automatedconcreteexposedreinforcementandcorrosiondetectionandmeasurementusingcolouredillumination AT zhangfeng automatedconcreteexposedreinforcementandcorrosiondetectionandmeasurementusingcolouredillumination |