Ju-ho Jung, Da-hyeon Kim, Chul-su Kim, Ryum-duck Oh, Jun-ho Ahn, Journal of Internet Computing and Services, Vol. 21, No. 4, pp. 109-116, Aug. 2020
10.7472/jksii.2020.21.4.109, Full Text:
Keywords: Rapid-transit railway, Railway, Deep Learning, Fusion

Abstract

With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.

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