An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges

As cracks on concrete bridges become severer and more frequent, methods of detecting cracks on concrete bridges have aroused great concern. Conventional methods, e.g., manual detection and equipment-aided detection, suffer from subjectivity and inefficiency, which increases demands for an accurate a...

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Main Authors: Qingfei Gao, Yu Wang, Jun Li, Kejian Sheng, Chenguang Liu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/2020/8896176
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author Qingfei Gao
Yu Wang
Jun Li
Kejian Sheng
Chenguang Liu
author_facet Qingfei Gao
Yu Wang
Jun Li
Kejian Sheng
Chenguang Liu
author_sort Qingfei Gao
collection DOAJ
description As cracks on concrete bridges become severer and more frequent, methods of detecting cracks on concrete bridges have aroused great concern. Conventional methods, e.g., manual detection and equipment-aided detection, suffer from subjectivity and inefficiency, which increases demands for an accurate and efficient method to detect bridge cracks. To this end, we modify the existing percolation method and propose an enhanced percolation method, which detects cracks of concrete bridges automatically. The modification includes three improvements, which are (1) employing photo expansion to eliminate boundary effects, (2) varying shape factors to increase the accuracy of percolating unclear cracks, and (3) decreasing the number of neighbouring pixels to form candidate sets. Combined with the above three improvements, three versions of enhanced percolation methods utilizing three different shape factors are put forward. The numerical experiment on detecting cracks in 200 images of the bridge surface demonstrates the outperformance of the enhanced percolation method in precision, recall, F-1 score, and time compared with traditional detecting methods. The proposed method can be generalized on the application of detecting other types of bridge diseases, which is an advantage for designing, maintaining, and restoring infrastructures.
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institution Kabale University
issn 1687-8086
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language English
publishDate 2020-01-01
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spelling doaj-art-2b2723ab656746518a02f198cc4e8f892025-08-20T03:54:43ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88961768896176An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete BridgesQingfei Gao0Yu Wang1Jun Li2Kejian Sheng3Chenguang Liu4School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, ChinaSchool of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, ChinaDepartment of Municipal and Environmental Engineering, Heilongjiang Institute of Construction Technology, Harbin 150050, ChinaCollege of Civil and Architectural Engineering, Heilongjiang Institute of Technology, Harbin 150050, ChinaSchool of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215000, ChinaAs cracks on concrete bridges become severer and more frequent, methods of detecting cracks on concrete bridges have aroused great concern. Conventional methods, e.g., manual detection and equipment-aided detection, suffer from subjectivity and inefficiency, which increases demands for an accurate and efficient method to detect bridge cracks. To this end, we modify the existing percolation method and propose an enhanced percolation method, which detects cracks of concrete bridges automatically. The modification includes three improvements, which are (1) employing photo expansion to eliminate boundary effects, (2) varying shape factors to increase the accuracy of percolating unclear cracks, and (3) decreasing the number of neighbouring pixels to form candidate sets. Combined with the above three improvements, three versions of enhanced percolation methods utilizing three different shape factors are put forward. The numerical experiment on detecting cracks in 200 images of the bridge surface demonstrates the outperformance of the enhanced percolation method in precision, recall, F-1 score, and time compared with traditional detecting methods. The proposed method can be generalized on the application of detecting other types of bridge diseases, which is an advantage for designing, maintaining, and restoring infrastructures.http://dx.doi.org/10.1155/2020/8896176
spellingShingle Qingfei Gao
Yu Wang
Jun Li
Kejian Sheng
Chenguang Liu
An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges
Advances in Civil Engineering
title An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges
title_full An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges
title_fullStr An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges
title_full_unstemmed An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges
title_short An Enhanced Percolation Method for Automatic Detection of Cracks in Concrete Bridges
title_sort enhanced percolation method for automatic detection of cracks in concrete bridges
url http://dx.doi.org/10.1155/2020/8896176
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