Semi-automatic crack width measurement using an OrthoBoundary algorithm

Zhe Li; Yi Miao; Mehran Eskandari Torbaghan; Hongfei  Zhang; Jiupeng  Zhang

doi:10.1016/j.autcon.2023.105251

Semi-automatic crack width measurement using an OrthoBoundary algorithm

Zhe Li, Yi Miao, Mehran Eskandari Torbaghan^*, Hongfei Zhang, Jiupeng Zhang^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Evaluation of pavements' crack severity levels currently relies heavily on width measurement, which necessitates the development of a rapid, and high-accurate, automatic measurement approach for complex pavement cracks. This paper presents an OrthoBoundary algorithm that leverages the crack boundary and skeleton directions to determine crack propagation. Comparative analysis has been conducted between OrthoBoundary and Area-Length, Skeleton Shortest Distance (SSD), Edge Shortest Distance (ESD), and Orthogonal Projection (OP) methods. Results indicate that the OrthoBoundary algorithm achieves an average accuracy of 90.10%, outperforming the Area-Length (86.60%), SSD (76.01%), ESD (87.24%), and OP (88.07%) methods. Notably, the OrthoBoundary algorithm also exhibits processing speeds approximately 120 times faster than other considered methods while demonstrating improved robustness and user-friendliness. It has significant potential to quantify and assess the severity of pavement cracks, as well as to facilitate maintenance decision-making processes in road infrastructure management systems.

Original language	English
Article number	105251
Number of pages	17
Journal	Automation in Construction
Volume	158
Early online date	26 Dec 2023
DOIs	https://doi.org/10.1016/j.autcon.2023.105251
Publication status	Published - Feb 2024

Bibliographical note

Acknowledgments:
This study was supported by the National Natural Science Foundation of China (No. 51978068), Natural Science Foundation of Shaanxi Province (No. 2020JM-217). The authors gratefully acknowledge their financial support. The first author would also like to acknowledge the China Scholarship Council (CSC) for supporting his visit to University of Birmingham, UK (No. 202106560034).

Keywords

Pavement crack
Width measurement
Orthogonal projection
Principal component analysis
Skeleton

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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LiZ2023Semi
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1 Article

An Automated 3D Crack Severity Assessment Using Surface Data for Improving Flexible Pavement Maintenance Strategies
Li, Z., Eskandari Torbaghan, M., Zhang, T., Qin, X., Li, W., Li, Y. & Zhang, J., 4 Apr 2024, (E-pub ahead of print) In: IEEE Transactions on Intelligent Transportation Systems .
Research output: Contribution to journal › Article › peer-review

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Cite this

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title = "Semi-automatic crack width measurement using an OrthoBoundary algorithm",

abstract = "Evaluation of pavements' crack severity levels currently relies heavily on width measurement, which necessitates the development of a rapid, and high-accurate, automatic measurement approach for complex pavement cracks. This paper presents an OrthoBoundary algorithm that leverages the crack boundary and skeleton directions to determine crack propagation. Comparative analysis has been conducted between OrthoBoundary and Area-Length, Skeleton Shortest Distance (SSD), Edge Shortest Distance (ESD), and Orthogonal Projection (OP) methods. Results indicate that the OrthoBoundary algorithm achieves an average accuracy of 90.10%, outperforming the Area-Length (86.60%), SSD (76.01%), ESD (87.24%), and OP (88.07%) methods. Notably, the OrthoBoundary algorithm also exhibits processing speeds approximately 120 times faster than other considered methods while demonstrating improved robustness and user-friendliness. It has significant potential to quantify and assess the severity of pavement cracks, as well as to facilitate maintenance decision-making processes in road infrastructure management systems.",

keywords = "Pavement crack, Width measurement, Orthogonal projection, Principal component analysis, Skeleton",

author = "Zhe Li and Yi Miao and {Eskandari Torbaghan}, Mehran and Hongfei Zhang and Jiupeng Zhang",

note = "Acknowledgments: This study was supported by the National Natural Science Foundation of China (No. 51978068), Natural Science Foundation of Shaanxi Province (No. 2020JM-217). The authors gratefully acknowledge their financial support. The first author would also like to acknowledge the China Scholarship Council (CSC) for supporting his visit to University of Birmingham, UK (No. 202106560034).",

year = "2024",

month = feb,

doi = "10.1016/j.autcon.2023.105251",

language = "English",

volume = "158",

journal = "Automation in Construction",

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T1 - Semi-automatic crack width measurement using an OrthoBoundary algorithm

AU - Li, Zhe

AU - Miao, Yi

AU - Eskandari Torbaghan, Mehran

AU - Zhang, Hongfei

AU - Zhang, Jiupeng

N1 - Acknowledgments: This study was supported by the National Natural Science Foundation of China (No. 51978068), Natural Science Foundation of Shaanxi Province (No. 2020JM-217). The authors gratefully acknowledge their financial support. The first author would also like to acknowledge the China Scholarship Council (CSC) for supporting his visit to University of Birmingham, UK (No. 202106560034).

PY - 2024/2

Y1 - 2024/2

N2 - Evaluation of pavements' crack severity levels currently relies heavily on width measurement, which necessitates the development of a rapid, and high-accurate, automatic measurement approach for complex pavement cracks. This paper presents an OrthoBoundary algorithm that leverages the crack boundary and skeleton directions to determine crack propagation. Comparative analysis has been conducted between OrthoBoundary and Area-Length, Skeleton Shortest Distance (SSD), Edge Shortest Distance (ESD), and Orthogonal Projection (OP) methods. Results indicate that the OrthoBoundary algorithm achieves an average accuracy of 90.10%, outperforming the Area-Length (86.60%), SSD (76.01%), ESD (87.24%), and OP (88.07%) methods. Notably, the OrthoBoundary algorithm also exhibits processing speeds approximately 120 times faster than other considered methods while demonstrating improved robustness and user-friendliness. It has significant potential to quantify and assess the severity of pavement cracks, as well as to facilitate maintenance decision-making processes in road infrastructure management systems.

AB - Evaluation of pavements' crack severity levels currently relies heavily on width measurement, which necessitates the development of a rapid, and high-accurate, automatic measurement approach for complex pavement cracks. This paper presents an OrthoBoundary algorithm that leverages the crack boundary and skeleton directions to determine crack propagation. Comparative analysis has been conducted between OrthoBoundary and Area-Length, Skeleton Shortest Distance (SSD), Edge Shortest Distance (ESD), and Orthogonal Projection (OP) methods. Results indicate that the OrthoBoundary algorithm achieves an average accuracy of 90.10%, outperforming the Area-Length (86.60%), SSD (76.01%), ESD (87.24%), and OP (88.07%) methods. Notably, the OrthoBoundary algorithm also exhibits processing speeds approximately 120 times faster than other considered methods while demonstrating improved robustness and user-friendliness. It has significant potential to quantify and assess the severity of pavement cracks, as well as to facilitate maintenance decision-making processes in road infrastructure management systems.

KW - Pavement crack

KW - Width measurement

KW - Orthogonal projection

KW - Principal component analysis

KW - Skeleton

U2 - 10.1016/j.autcon.2023.105251

DO - 10.1016/j.autcon.2023.105251

M3 - Article

SN - 0926-5805

VL - 158

JO - Automation in Construction

JF - Automation in Construction

M1 - 105251

ER -

Semi-automatic crack width measurement using an OrthoBoundary algorithm

Abstract

Bibliographical note

Keywords

UN SDGs

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Research output

An Automated 3D Crack Severity Assessment Using Surface Data for Improving Flexible Pavement Maintenance Strategies

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