Abstract
Obstacles detection systems are essential to obtain a higher safety level on railways. Such systems has the ability to contribute to the development of automated guided trains. Even though some laser equipments have been used to detect obstacles, short detection distance and low accuracy on curve zones make them not the best solution. In this paper, after an assessment of the risks related to railway accidents and their possible causes, computer vision combined with prior knowledge is used to develop an innovative approach. A function to find the starting point of the rails is proposed. After that, bottom-up adaptive windows are created to focus on the region of interest and ignore the background. The whole system can run in real time thanks to its linear complexity. Experimental tests demonstrated that the system performs well in different conditions.
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Wang, H., Zhang, X., Damiani, L., Giribone, P., Revetria, R., Ronchetti, G. (2018). Transportation Safety Improvements Through Video Analysis: An Application of Obstacles and Collision Detection Applied to Railways and Roads. In: Ao, SI., Kim, H., Castillo, O., Chan, AS., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2017. Springer, Singapore. https://doi.org/10.1007/978-981-10-7488-2_1
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DOI: https://doi.org/10.1007/978-981-10-7488-2_1
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