• Laser & Optoelectronics Progress
  • Vol. 57, Issue 22, 221023 (2020)
Jiewen Yang1, Guang Zhang1, Xijiang Chen1、*, and Ya Ban2
Author Affiliations
  • 1School of Safety & Emergency Management, Wuhan University of Technology, Wuhan, Hubei 430079, China;
  • 2Chongqing Academic of Measurement and Quality Inspection, Chongqing 404100, China
  • show less
    DOI: 10.3788/LOP57.221023 Cite this Article Set citation alerts
    Jiewen Yang, Guang Zhang, Xijiang Chen, Ya Ban. Quantitative Identification of Concrete Surface Cracks Based on Deep Learning Clustering Segmentation and Morphology[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221023 Copy Citation Text show less
    References

    [1] Zhu H C, Tong Y J, Ji T et al. Elimination technology of noise introduced by top-up injection in synchrotron radiation infrared beamline[J]. Journal of Infrared and Millimeter Waves, 37, 251-257(2018).

    [2] Chen Z G, Li Y G, Chen X F et al. Edge and texture detection of metal image under high temperature and dynamic solidification condition[J]. Journal of Central South University, 25, 1501-1512(2018).

    [3] Wen N, Yang S Z, Zhu C J et al. Adaptive contourlet-wavelet iterative shrinkage/thresholding for remote sensing image restoration[J]. Journal of Zhejiang University SCIENCE C, 15, 664-674(2014).

    [4] Wang G L, Zhang X H, Han Y C et al. Automatic multi-region segmentation of intracoronary optical coherence tomography images based on neutrosophic theory[J]. Journal of Biomedical Engineering, 36, 59-67(2019).

    [5] Lin L K, Wang S Y, Tang Z X. Point target detection in infrared over-sampling scanning images using deep convolutional neural networks[J]. Journal of Infrared and Millimeter Waves, 37, 219-226(2018).

    [6] Wu Q P, Wu C M. A fast and robust clustering segmentation algorithm for kernel space graphics[J]. CAAI Transactions on Intelligent Systems, 14, 804-811(2019).

    [7] Sun W H, Li Q K, Shao T F et al. Crack detection algorithm of protective wall for piles based on machine vision[J]. Computer Engineering and Applications, 55, 260-265(2019).

    [8] Xiao L F, Zhou D Y. Application of Sobel operator improved edge detection algorithm in concrete crack identification[J]. Software Guide, 16, 112-114(2017).

    [9] Han Y, Sun H, Li L et al. Design and implementation of rapid inspection system for building surface crack based on UAV[J]. Journal of Civil Engineering and Management, 36, 60-65(2019).

    [10] Shao C, Wang S H, Xu F H et al. Research on concrete surface crack detection based on image processing[J]. Journal of Hubei University of Automotive Technology, 33, 47-50, 59(2019).

    [11] Qu Z, Chen Y X. Concrete surface cracks detecting algorithm based on improved genetic programming[J]. Computer Engineering and Design, 40, 1660-1664(2019).

    [12] Liu X G, Chen Y Y, Zhu A X et al. Tunnel crack identification based on deep learning[J]. Journal of Guangxi University (Natural Science Edition), 43, 2243-2251(2018).

    [13] Cha Y J, Choi W, Büyüköztürk O. Deep learning-based crack damage detection using convolutional neural networks[J]. Computer-Aided Civil and Infrastructure Engineering, 32, 361-378(2017).

    [14] Wang S, Wu X, Zhang Y H et al. Image crack detection with fully convolutional network based on deep learning[J]. Journal of Computer-Aided Design & Computer Graphics, 30, 859-867(2018).

    [15] Xue Y D, Li Y C. A method of disease recognition for shield tunnel lining based on deep learning[J]. Journal of Hunan University (Natural Sciences), 45, 100-109(2018).

    [16] Qiu C G, Kong L F, Yang S H. Automatic recognition of flavor types of flue-cured tobacco based on GA-SVM algorithm[J]. Tobacco Science and Technology, 52, 101-108(2019).

    [17] Li H G, Lian Y, Fang M Q. Entropy-based dynamic particle swarm optimization algorithm[J]. Journal of Beijing University of Technology, 41, 657-661(2015).

    [18] Tang L L, Yu Z W, Ren C et al. Information acquisition method of three-dimensional intersection spatial structure based on vehicle GPS trajectory[J]. Journal of Traffic and Transportation Engineering, 19, 170-179(2019).

    [19] Li Z J, Jiang X J, Zhu Z T et al[J]. Bullet defect detection method based on deep learning Modular Machine Tool & Automatic Manufacturing Technique, 2019, 102-106, 110.

    [20] Lu Q J. An improved two-dimensional otsu image segmentation algorithm[J]. Natural Science Journal of Xiangtan University, 40, 82-87(2018).

    [21] Zhao F, Zhou W H, Chen Y T et al. Application of improved canny operator in crack detection[J]. Electronic Measurement Technology, 41, 107-111(2018).

    [22] Yang X F, Zhao L, Du J J. The pipeline's crack detection algorithm based on improved Median filtering and morphology[J]. Computer Simulation, 35, 81-85, 180(2018).

    [23] Wang Y Y, Yu G. Image edge detection of joint K-means and morphological operator[J]. Ship Electronic Engineering, 39, 105-107, 156(2019).

    [24] 3. 4(3):, 172, 175(2019).

    [25] Feng G Z, Ni M Y, Ou S F et al. A preferential interval-valued fuzzy C-means algorithm for remotely sensed imagery classification[J]. International Journal of Fuzzy Systems, 21, 2212-2222(2019).

    Jiewen Yang, Guang Zhang, Xijiang Chen, Ya Ban. Quantitative Identification of Concrete Surface Cracks Based on Deep Learning Clustering Segmentation and Morphology[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221023
    Download Citation