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Automatic Detection of Rail Defects from Images

In: Intelligent Quality Assessment of Railway Switches and Crossings

Author

Listed:
  • Emil Hovad

    (Technical University of Denmark)

  • Helena Hansen

    (Technical University of Denmark)

  • André Filipe Silva Rodrigues

    (Banedanmark)

  • Vedrana Andersen Dahl

    (Technical University of Denmark)

Abstract

In this study, images of the rails captured by a track recording car are investigated. The images are processed in order to asses and predict the rail quality by a simple method, which gives the possibility of fast and easy implementation. The first step of the method is detecting the rails from the images with an algorithm. The second step of the method is finding visually noticeable defects on the detected rail with automatized algorithms for defect detection. One of the algorithms for defect detection shows promising results and investigating the rail images could be a promising complementary method to the already used manual ultrasound measurements.

Suggested Citation

  • Emil Hovad & Helena Hansen & André Filipe Silva Rodrigues & Vedrana Andersen Dahl, 2021. "Automatic Detection of Rail Defects from Images," Springer Series in Reliability Engineering, in: Roberto Galeazzi & Hilmar Kjartansson Danielsen & Bjarne Kjær Ersbøll & Dorte Juul Jensen & Ilmar Sa (ed.), Intelligent Quality Assessment of Railway Switches and Crossings, pages 187-205, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-62472-9_11
    DOI: 10.1007/978-3-030-62472-9_11
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