Crack property identification on concrete construction surface using an automatic image-based measurement

被引：0
|
作者：
Peng Q.H. [1 ]
Huang W. [2 ]
Sun Q. [1 ]
Lu Y. [2 ]
Zhang Z. [2 ]
机构：
[1] College of Information System and Management, National University of Defense Technology, Changsha, Hunan
[2] College of Commander Basic Education, National University of Defense Technology, Changsha, Hunan
来源：
Peng, Qizi Huang | 1600年 / American Scientific Publishers卷 / 13期
关键词：
Concrete construction; Crack property; Image-based measurement; Non-destructive measurement; Safety evaluation;
D O I：
10.1166/jctn.2016.4996
中图分类号：
学科分类号：
摘要：
The safety of concrete construction is evaluated manually by inspecting visible damage in structural elements. However, this process is time consuming and costly. To automate this assessment, a nondestructive photogrammetric has been widely used for damage identification in civil engineering. One of the most common damage types is concrete surface crack. Therefore, this study proposes a novel image-based measurement of crack properties in concrete construction. The method first retrieves the crack skeleton and profile from the crack map generated by pre-processing the original image. Then, the crack skeleton is abstracted into a tree structure, and small edges from the crack trunk are removed to calculate the length of the crack. Finally, Euclidian distance transform is applied on the crack profile to calculate the width of the crack. The proposed method can identify crack properties automatically and enhance stability, durability, and safety evaluation of the concrete construction. Validity and accuracy are tested by experiments on crack images of real concrete construction. Copyright © 2016 American Scientific Publishers All rights reserved.
引用
收藏
页码：3337 / 3344
页数：7
相关论文
共 50 条
  • [1] Image-Based Framework for Concrete Surface Crack Monitoring and Quantification
    Chen, ZhiQiang
    Hutchinson, Tara C.
    ADVANCES IN CIVIL ENGINEERING, 2010, 2010
  • [2] Crack measurement: Development, testing and applications of an automatic image-based algorithm
    Barazzetti, Luigi
    Scaioni, Marco
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2009, 64 (03) : 285 - 296
  • [3] Image-based crack detection for real concrete surfaces
    Yamaguchi, Tomoyuki
    Nakamura, Shingo
    Saegusa, Ryo
    Hashimoto, Shuji
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2008, 3 (01) : 128 - 135
  • [4] Image-Based Concrete Crack Detection Method Using the Median Absolute Deviation
    Avendano, Juan Camilo
    Leander, John
    Karoumi, Raid
    SENSORS, 2024, 24 (09)
  • [5] Robust Image-Based Surface Crack Detection Using Range Data
    Zhou, Shanglian
    Song, Wei
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2020, 34 (02)
  • [6] Automatic bridge crack identification from concrete surface using ResNeXt with postprocessing
    Li, Gang
    Ren, Xueli
    Qiao, Wenting
    Ma, Biao
    Li, Ying
    STRUCTURAL CONTROL & HEALTH MONITORING, 2020, 27 (11):
  • [7] Image-based identification procedure of a crack propagation law
    Mathieu, Florent
    Hild, Francois
    Roux, Stephane
    ENGINEERING FRACTURE MECHANICS, 2013, 103 : 48 - 59
  • [8] An Image-based Automatic Calculation Algorithm for Bridge Crack Size
    Wang, Qi
    Dong, Xisong
    Shen, Zhen
    Xiong, Gang
    Yan, Jun
    Niu, Lulu
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 1109 - 1114
  • [9] Image-based retrieval of concrete crack properties for bridge inspection
    Adhikari, R. S.
    Moselhi, O.
    Bagchi, A.
    AUTOMATION IN CONSTRUCTION, 2014, 39 : 180 - 194
  • [10] Image-based concrete crack detection in tunnels using deep fully convolutional networks
    Ren, Yupeng
    Huang, Jisheng
    Hong, Zhiyou
    Lu, Wei
    Yin, Jun
    Zou, Lejun
    Shen, Xiaohua
    CONSTRUCTION AND BUILDING MATERIALS, 2020, 234 (234)
12345