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Automatic Detection of Obstacles in Railway Tracks Using Monocular Camera

  • Guilherme Kano
  • Tiago Andrade
  • Alexandra MoutinhoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11754)

Abstract

This paper presents an algorithm for automatic detection of obstructions on railway tracks. Based on computer vision techniques, this algorithm extracts the railway tracks from the image feed and automatically detects obstacles that can endanger normal railway system operation, as well as the safety of its users. To segment the railway tracks, two techniques are explored. First, the Hough transform is used to detect straight lines, which proves to be inefficient when dealing with curves. To overcome this problem, an alternative solution is developed based on mathematical morphology techniques and BLOB (Binary Large OBject) analysis, leading to a more robust segmentation. The surrounding terrain is also subject to analysis. The algorithm’s performance is evaluated considering different scenarios with and without simulated anomalies, demonstrating the effectiveness of the proposed solution.

Keywords

Railway obstruction detection Monocular camera Computer vision 

Notes

Acknowledgements

This research is funded by FCT, through IDMEC, under LAETA, project UID/EMS/50022/2019.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Instituto Superior TécnicoUniversidade de LisboaLisboaPortugal
  2. 2.IDMEC, Instituto Superior TécnicoUniversidade de LisboaLisboaPortugal

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