Affiliation:
1. Polytechnic School , University of Palermo 90100 , Palermo , Italy
Abstract
Abstract
Nowadays safety in railways is mostly achieved by automated system technologies such as ERTMS/ETCS. Nevertheless, on local railways (suburban and regional lines) several tasks still depend on the choices and actions of a human crew. With the aim to improve safety in such type of railways, this research proposes a system for the automatic detection and recognition of railway signs by means of the digital image processing technique. First field applications, carried out on the Italian railway network, show that the proposed system is very accurate (the percentage of correctly detected railway signs is about 97%), even at high train speeds.
Subject
Computer Science Applications,General Engineering
Reference20 articles.
1. 1. Bruno, L., Parla, G., Celauro, C. (2012) Improved Traffic Signal Detection and Classification via Image Processing Algorithms. Procedia - Social and Behavioral Sciences (53), 811–821. https://doi.org/10.1016/j.sbspro.2012.09.93010.1016/j.sbspro.2012.09.930
2. 2. De La Escalera, A., Armingol, J. M. A., Mata, M. (2003) Traffic sign recognition and analysis for intelligent vehicles. Image and vision computing, 21, 247–258. - https://doi.org/10.1016/S0262-8856(02)00156-710.1016/S0262-8856(02)00156-7
3. 3. Delfino, A., Galaverna, M. (2003) Mobile and fixed block: Carrying capacity analysis. Ingegneria Ferroviaria 6: 555-565.
4. 4. Directive 2004/49/EC, Commission Directive 2009/149/EC and Regulation (EC) No 91/2003.
5. 1. ERA. Railway Safety Performance in the European Union. Biennial Report. European Union Agency for railway, 2016.
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