Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0215009(2021)

Rail Surface Damage Detection Method Based on Improved U-Net Convolutional Neural Network

Bo Liang, Jun Lu*, and Yang Cao
Author Affiliations
  • College of Mechanical & Electrical Engineering, Shaanxi University of Science and Technology, Xi'an, Shaanxi 710021, China
  • show less
    References(16)

    [5] Chen P H, Ho S S. Is overfeat useful for image-based surface defect classification tasks?. [C]∥2016 IEEE International Conference on Image Processing (ICIP), September 25-28, 2016, Phoenix, AZ, USA. New York: IEEE, 749-753(2016).

    [7] Li Q Y, Tan Y Q, Zhang H Y et al. A visual inspection system for rail corrugation based on local frequency features. [C]∥2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Scien, 18-23(2016).

    [9] Trinh H, Haas N, Li Y et al. Enhanced rail component detection and consolidation for rail track inspection. [C]∥2012 IEEE Workshop on the Applications of Computer Vision (WACV), January 9-11, 2012, Breckenridge, CO, USA. New York: IEEE, 289-295(2012).

    [11] Li Q Y, Ren S W. A visual detection system for rail surface defects[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42, 1531-1542(2012).

    [12] He Z D, Wang Y N, Yin F et al. Surface defect detection for high-speed rails using an inverse P-M diffusion model[J]. Sensor Review, 36, 86-97(2016).

    [13] Gan J R, Li Q Y, Wang J Z et al. A hierarchical extractor-based visual rail surface inspection system[J]. IEEE Sensors Journal, 17, 7935-7944(2017).

    [14] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. ∥Navab N, Hornegger J, Wells W, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science. Cham: Springer, 9351, 234-241(2015).

    [15] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 3431-3440(2015).

    [16] Huang Y, Qiu C, Yuan K. Surface defect saliency of magnetic tile[J]. The Visual Computer, 36, 85-96(2020).

    Tools

    Get Citation

    Copy Citation Text

    Bo Liang, Jun Lu, Yang Cao. Rail Surface Damage Detection Method Based on Improved U-Net Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0215009

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Jun. 5, 2020

    Accepted: Aug. 3, 2020

    Published Online: Jan. 11, 2021

    The Author Email: Lu Jun (lujun@sust.edu.cn)

    DOI:10.3788/LOP202158.0215009

    Topics