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A. Atahouet, C. Lelionnais, "Railway track detection for train geographic location based on computer vision", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 15.3, 2022, doi:10.4203/ccc.1.15.3

Keywords: computer vision, railway detection, rail signalling, geographic location, gradient analysis, hough transform.

Abstract

In a railway infrastructure, train geographic location (e.g., GPS) must be strengthened to adapt to the network topology (i.e., inside or outside the station, straight or curved line, passages through tunnels). Alternative solutions must be proposed to meet this need. Computer vision is one of these disruptive answers to tackle this challenge. Indeed, this technology gives meaning to geographic location by getting closer to human behaviour (i.e., human eye). This paper presents an approach detecting the rails solely by computer vision and the knowledge of certain dimensions of the railway. A case

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 1 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 15.3 Railway track detection for train geographic location based on computer vision A. Atahouet and C. Lelionnais SNCF, Rolling Stock Engineering, France doi:10.4203/ccc.1.15.3 Full Bibliographic Reference for this paper A. Atahouet, C. Lelionnais, "Railway track detection for train geographic location based on computer vision", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 15.3, 2022, doi:10.4203/ccc.1.15.3 Keywords: computer vision, railway detection, rail signalling, geographic location, gradient analysis, hough transform. Abstract In a railway infrastructure, train geographic location (e.g., GPS) must be strengthened to adapt to the network topology (i.e., inside or outside the station, straight or curved line, passages through tunnels). Alternative solutions must be proposed to meet this need. Computer vision is one of these disruptive answers to tackle this challenge. Indeed, this technology gives meaning to geographic location by getting closer to human behaviour (i.e., human eye). This paper presents an approach detecting the rails solely by computer vision and the knowledge of certain dimensions of the railway. A case download the full-text of this paper (PDF, 365 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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