A Method of Lane Detection and Tracking for Expressway Based on RANSAC

被引:0
|
作者
Zhu, Shuliang [1 ,2 ]
Wang, Jianqiang [1 ]
Yu, Tao [2 ]
Wang, Jiao [2 ]
机构
[1] Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China
[2] Yantai Univ, Sch Electromech Automobile Engn, Yantai 264005, Peoples R China
来源
2017 2ND INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC 2017) | 2017年
基金
中国国家自然科学基金;
关键词
Lane detection; local otsu; window scanning; RANSAC;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Lane mark detection and tracking is essential for advanced driver assistance systems. We propose a computationally efficient lane mark detection and tracking method for expressway that can robustly and accurately detect la ne marks in an image. A small size detection window scanner moving in the region of interest to determine whether there is a lane mark at the current position. This method can improve the detection accuracy and noise immunity. According to the correlations between video frames, we locate la ne mark positions fast in current frame. We use an improved RANSAC method to fit the detected lane marks to straight lines. The proposed method is proved to be efficient through experiments for various complex environments.
引用
收藏
页码:62 / 66
页数:5
相关论文
共 50 条
  • [1] Lane Detection Method Based on Improved RANSAC Algorithm
    Guo, Jie
    Wei, Zhihua
    Miao, Duoqian
    2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON AUTONOMOUS DECENTRALIZED SYSTEMS ISADS 2015, 2015, : 285 - 288
  • [2] ROBUST LANE DETECTION AND TRACKING WITH RANSAC AND KALMAN FILTER
    Borkar, Amol
    Hayes, Monson
    Smith, Mark T.
    2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, : 3261 - +
  • [3] LANE DETECTION BASED ON GUIDED RANSAC
    Hu, Yi
    Kim, You-Sun
    Lee, Kwang-Wook
    Ko, Sung-Jea
    VISAPP 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 1, 2010, : 457 - 460
  • [4] Detection of lane markings based on ridgeness and RANSAC
    López, A
    Cañero, C
    Serrat, J
    Saludes, J
    Lumbreras, F
    Graf, T
    2005 IEEE Intelligent Transportation Systems Conference (ITSC), 2005, : 733 - 738
  • [5] A Lane Detection Method Based on a Ridge Detector and Regional G-RANSAC
    Lu, Zefeng
    Xu, Ying
    Shan, Xin
    Liu, Licai
    Wang, Xingzheng
    Shen, Jianhao
    SENSORS, 2019, 19 (18)
  • [6] Lane Detection Algorithm Based on Density Clustering and RANSAC
    Wang, Jitong
    Hong, Wei
    Gong, Lei
    PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 919 - 924
  • [7] A Lane Detection Method Combined Fuzzy Control with RANSAC Algorithm
    Xu, Y.
    Shan, X.
    Chen, B. Y.
    Chi, C.
    Lu, Z. F.
    Wang, Y. Q.
    2017 7TH INTERNATIONAL CONFERENCE ON POWER ELECTRONICS SYSTEMS AND APPLICATIONS - SMART MOBILITY, POWER TRANSFER & SECURITY (PESA), 2017,
  • [8] Lane Detection and Tracking based on Best Pairs of Lane Markings: Method and Evaluation
    Yeniaydin, Yasin
    Schmidt, Klaus Werner
    2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2020,
  • [9] A robust lane detection and tracking method based on computer vision
    Zhou, Yong
    Xu, Rong
    Hu, Xiaofeng
    Ye, Qingtai
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2006, 17 (04) : 736 - 745
  • [10] A novel curve lane detection based on Improved River Flow and RANSAC
    Tan, Huachun
    Zhou, Yang
    Zhu, Yong
    Yao, Danya
    Li, Keqiang
    2014 IEEE 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2014, : 133 - 138