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Engineering-oriented automated crack inspection and maximum-width quantification using MSCrack

delete2026-09-18
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PRE
AI
Y
Yangyang Tai
G
Gao Ma *
H
Hyeon‐Jong Hwang
Y
Yun Zhou
Z
Zengxi Wu
X
Xiaojing Tan
DOI:10.1016/j.measurement.2026.123242delete
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Abstract

Abstract

En 中文
• An image-based workflow is proposed for automated crack-width measurement. • MSCrack achieves competitive segmentation with only 3.704 M parameters. • Automated maximum crack-width extraction uses skeleton analysis and EDT.. • Validation on 104 field images yielded an MAE of 0.0081 mm and an MRE of 3.98 %. • Point-level 2D-3D mapping supports approximate facade crack localization.
Keywords:
Automated crack inspection
Lightweight crack segmentation
Image-derived crack-width measurement
2D–3D crack mapping
Structural condition assessment

Journal

Measurement cover
Measurement
IF:
5.6
Papers:
2.1W
Citations:
5.4W

Organization

S
seoul national university
Scholars:
6.5K
Papers: 2.4K
Citations: 0
H
hunan university
Scholars:
4.5W
Papers: 3.3W
Citations: 70
T
taike technology co ltd
Scholars:
2
Papers: 1
Citations: 0
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Cited Papers

Cited Papers

Review on computer vision-based crack detection and quantification methodologies for civil structures
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TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers
err2024-10-01
err26
errOAAI
errChen, Jieneng; Mei, Jieru; Li, Xianhang; Lu, Yongyi; Yu, Qihang; Wei, Qingyue; Luo, Xiangde; Xie, Yutong; Adeli, Ehsan; Wang, Yan; Lungren, Matthew P.; Zhang, Shaoting; Xing, Lei; Lu, Le; Yuille, Alan; Zhou, Yuyin
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DeepCrack: A deep hierarchical feature learning architecture for crack segmentation
err2019-04-01
err633
PREAI
errLiu, Yahui; Yao, Jian; Lu, Xiaohu; Xie, Renping; Li, Li
errShare
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researcher View more