Robust Road Lane Detection using Extremal-Region Enhancement

被引:0
作者
Gu, Jingchen [1 ,2 ]
Zhang, Qieshi [3 ]
Kamata, Sei-ichiro [1 ]
机构
[1] Waseda Univ, Grad Sch Informat Prod & Syst, Tokyo, Japan
[2] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200030, Peoples R China
[3] Waseda Univ, Fac Sci & Engn, Tokyo, Japan
来源
PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015 | 2015年
关键词
TRACKING; SYSTEM;
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
Road lane detection is a key problem in advanced driver-assistance systems (ADAS). For solving this problem, vision-based detection methods are widely used and are generally focused on edge information. However, only using edge information leads to miss detection and error detection in various road conditions. In this paper, we propose a neighbor-based image conversion method, called extremal-region enhancement. The proposed method enhances the white lines in intensity, hence it is robust to shadows and illuminance changes. Both edge and shape information of white lines are extracted as lane features in the method. In addition, we implement a robust road lane detection algorithm using the extracted features and improve the correctness through probability tracking. The experimental result shows an average detection rate increase of 13.2% over existing works.
引用
收藏
页码:519 / 523
页数:5
相关论文
共 12 条
[1]   Robust vision based lane tracking using multiple cues and particle filtering [J].
Apostoloff, N ;
Zelinsky, A .
IEEE IV2003: INTELLIGENT VEHICLES SYMPOSIUM, PROCEEDINGS, 2003, :558-563
[2]   Intelligent vehicle applications worldwide [J].
Bishop, R .
IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 2000, 15 (01) :78-81
[3]   A Novel Lane Detection System With Efficient Ground Truth Generation [J].
Borkar, Amol ;
Hayes, Monson ;
Smith, Mark T. .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2012, 13 (01) :365-374
[4]   Color-based road detection in urban traffic scenes [J].
He, YH ;
Wang, H ;
Zhang, B .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2004, 5 (04) :309-318
[5]   Robust lane detection and tracking in challenging scenarios [J].
Kim, ZuWhan .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2008, 9 (01) :16-26
[6]   Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation [J].
McCall, JC ;
Trivedi, MM .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2006, 7 (01) :20-37
[7]   THRESHOLD SELECTION METHOD FROM GRAY-LEVEL HISTOGRAMS [J].
OTSU, N .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1979, 9 (01) :62-66
[8]  
Vacek S., 2006, 2006 IEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (IEEE Cat. No. 06TH8908), P203, DOI 10.1109/MFI.2006.265649
[9]   A novel system for robust lane detection and tracking [J].
Wang, Yifei ;
Dahnoun, Naim ;
Achim, Alin .
SIGNAL PROCESSING, 2012, 92 (02) :319-334
[10]   Three-feature based automatic lane detection algorithm (TFALDA) for autonomous driving [J].
Yim, YU ;
Oh, SY .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2003, 4 (04) :219-225