Real-Time Lane Marking Detection

被引：0
|
作者：
Filonenko, Alexander [1 ]
Hernandez, Danilo Caceres [1 ]
Kurnianggoro, Laksono [1 ]
Seo, Dongwook [1 ]
Jo, Kang-Hyun [1 ]
机构：
[1] Univ Ulsan, Grad Sch Elect Engn, Intelligent Syst Lab, Ulsan 680749, South Korea
来源：
2015 IEEE 2ND INTERNATIONAL CONFERENCE ON CYBERNETICS (CYBCONF) | 2015年
关键词：
Autonomous robot navigation; GPGPU; CUDA; lane detection; LEVEL;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
For autonomous navigation the real-time processing is crucial. This paper proposes a method to detect the lane markings in real-time using the advantage of parallel processing. A region of interest is constrained by the current velocity of a vehicle. The segmentation was achieved by utilizing a difference in color between lane marking and road pavement. The overall process is divided into three steps. The first is detection of lane markings based on the color probability. The second is the implementation of distance clustering analysis to define the surface course. Finally, The curve fitting was applied to assure the lane markings. The method was tested on a dataset to prove its effectiveness.
引用
收藏
页码：125 / 128
页数：4
相关论文
共 50 条
  • [1] Vision-Based Real-Time Lane Marking Detection and Tracking
    Liu, Wei
    Zhang, Hongliang
    Duan, Bobo
    Yuan, Huai
    Zhao, Hong
    [J]. PROCEEDINGS OF THE 11TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, 2008, : 49 - +
  • [2] Real-Time Global Localization of Robotic Cars in Lane Level via Lane Marking Detection and Shape Registration
    Cui, Dixiao
    Xue, Jianru
    Zheng, Nanning
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (04) : 1039 - 1050
  • [3] A real-time lane marking localization, tracking and communication system
    Mammeri, Abdelhamid
    Boukerche, Azzedine
    Tang, Zongzhi
    [J]. COMPUTER COMMUNICATIONS, 2016, 73 : 132 - 143
  • [4] A Framework for Camera-Based Real-Time Lane and Road Surface Marking Detection and Recognition
    Gupta, Any
    Choudhary, Ayesha
    [J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2018, 3 (04): : 476 - 485
  • [5] A Real-Time Lane Detection and Tracking Algorithm
    Gao, Qi
    Feng, Yan
    Wang, Li
    [J]. PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC), 2017, : 1230 - 1234
  • [6] Real-time lane detection for autonomous vehicle
    Jeong, SG
    Kim, CS
    Lee, DY
    Ha, SK
    Lee, DH
    Lee, MH
    Hashimoto, H
    [J]. ISIE 2001: IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS PROCEEDINGS, VOLS I-III, 2001, : 1466 - 1471
  • [7] Real-time lane detection for autonomous navigation
    Jeong, SG
    Kim, CS
    Yoon, KS
    Lee, JN
    Bae, JI
    Lee, MH
    [J]. 2001 IEEE INTELLIGENT TRANSPORTATION SYSTEMS - PROCEEDINGS, 2001, : 508 - 513
  • [8] Real-Time Global Localization of Intelligent Road Vehicles in Lane-Level via Lane Marking Detection and Shape Registration
    Cui, Dixiao
    Xue, Jianru
    Du, Shaoyi
    Zheng, Nanning
    [J]. 2014 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2014), 2014, : 4958 - 4964
  • [9] Real-Time Road Lane Detection with Commodity Hardware
    Sakjiraphong, Somchok
    Pinho, Andre
    Dailey, Matthew N.
    Ekpanyapong, Mongkol
    Tavares, Adriano
    [J]. 2014 INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), 2014,
  • [10] Real-time lane and obstacle detection on the gold system
    Bertozzi, M
    Broggi, A
    [J]. PROCEEDINGS OF THE 1996 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 1996, : 213 - 218
12345