TY - GEN
T1 - Real-Time Rule-Based Algorithm for Track Detection of Tram-Train
AU - Baek, Jihyeon
AU - Kwak, Jaeho
AU - Hwang, Hyeon Chyeol
AU - Park, Sung Won
AU - Jeon, Heegyun
AU - Lee, Hyunsuk
AU - Kuc, Tae Yong
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Tram-Train is a form of rail transport that connects urban centers, suburbs, and small and medium-sized cities. It is characterized by the operation of light rail vehicles on the existing railway infrastructure, which runs on two different tracks. In this paper, we propose to detect the pair position of embedded rail and surface rail by fusing classical image analysis methods for Tram-Train track detection. The sliding window algorithm is used to estimate the rail's initial rail point, and the gradient value is used to detect the rail Our algorithm works in a rule-based method by exploiting railway tracks' invariant features, reducing unnecessary computations and improving accuracy. We experiment on a tram test line located in Osong-eup, Chungcheongbuk-do, South Korea. The experiment confirms that the proposed algorithm can detect tracks in real-time.
AB - Tram-Train is a form of rail transport that connects urban centers, suburbs, and small and medium-sized cities. It is characterized by the operation of light rail vehicles on the existing railway infrastructure, which runs on two different tracks. In this paper, we propose to detect the pair position of embedded rail and surface rail by fusing classical image analysis methods for Tram-Train track detection. The sliding window algorithm is used to estimate the rail's initial rail point, and the gradient value is used to detect the rail Our algorithm works in a rule-based method by exploiting railway tracks' invariant features, reducing unnecessary computations and improving accuracy. We experiment on a tram test line located in Osong-eup, Chungcheongbuk-do, South Korea. The experiment confirms that the proposed algorithm can detect tracks in real-time.
KW - Computer Vision
KW - Embedded rail
KW - Railway tracks detection
KW - Surface rail
KW - Tram-Train
UR - https://www.scopus.com/pages/publications/85213816633
U2 - 10.1109/RTSI61910.2024.10761626
DO - 10.1109/RTSI61910.2024.10761626
M3 - Conference contribution
AN - SCOPUS:85213816633
T3 - 8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024 - Proceeding
SP - 277
EP - 282
BT - 8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024
Y2 - 18 September 2024 through 20 September 2024
ER -
