[1]林国余,陈旭,张为公.基于多信息融合优化的鲁棒性车道检测算法[J].东南大学学报(自然科学版),2010,40(4):771-777.[doi:10.3969/j.issn.1001-0505.2010.04.021]
 Lin Guoyu,Chen Xu,Zhang Weigong.Robust lane detection algorithm based on multiple information fusion and optimizations[J].Journal of Southeast University (Natural Science Edition),2010,40(4):771-777.[doi:10.3969/j.issn.1001-0505.2010.04.021]
点击复制

基于多信息融合优化的鲁棒性车道检测算法()
分享到:

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第4期
页码:
771-777
栏目:
计算机科学与工程
出版日期:
2010-07-20

文章信息/Info

Title:
Robust lane detection algorithm based on multiple information fusion and optimizations
作者:
林国余1 陈旭2 张为公1
1 东南大学仪器科学与工程学院, 南京 210096; 2 南京信息工程大学信息与控制学院, 南京 210044
Author(s):
Lin Guoyu1 Chen Xu2 Zhang Weigong1
1 School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
2 School of Information and Communications Technologies, Nanjing University of Information Science and Technology, Nanjing 210044, China
关键词:
车道线检测 鲁棒性 多特征融合
Keywords:
lane detection robust multiple features fusion
分类号:
TP391.4
DOI:
10.3969/j.issn.1001-0505.2010.04.021
摘要:
为了提高复杂环境下车道线检测的鲁棒性,提出一种基于多特征信息融合优化的鲁棒性车道线检测算法.首先构建了基于二次曲线空间道路模型图像中左右车道线数学模型; 然后融合像素梯度值、梯度方向、像素灰度以及车道线结构等多特征信息,构造后验概率函数; 最后采用基于免疫克隆策略的改进粒子群优化算法优化车道线模型参数,实现车道线提取.对实际道路图像的实验结果表明,引入多特征信息后,在道路中存在阴影、车辆和道路标记等干扰因素,以及车道线模糊、对比度较低的情况下,该算法也能快速准确地提取车道线,具有很强的鲁棒性.
Abstract:
To improve the robustness of lane detection under complex conditions, a robust lane detection approach based on multiple information fusion optimizations is proposed. First based on the spatial quadratic road model, the left and right lane model expression in image plane is constructed. Then combined with the gradient value, gradient direction, gray information and road structure information, the expression of the posterior probability is derived. Finally the particle swarm optimization combined with immune clone strategy is used for calculating the model parameters. The results of the real road image experimentation show that after involving the multiple features information, the proposed method can robustly and rapidly detect the lane markings even if there are some interference factors in the road such as shadow, vehicle and land mark etc., as well as baded lane boundaries and relatively weak local contrast.

参考文献/References:

[1] Lee Joon Woong,Yi Un Kun.A lane-departure identification based on LBPE,Hough transform,and linear regression[J].Computer Vision and Image Understanding,2005,99(3):359-383.
[2] Zhu Wennan,Chen Qiang,Wang Hong.Lane detection in some complex conditions[C] //IEEE/RSJ International Conference on Intelligent Robots and Systems.Beijing,China,2006:117-122.
[3] Chen Qiang,Wang Hong.A real time lane detection algorithm based on a hyperbola-pair model[C] //IEEE Intelligent Vehicles Symposium.Tokyo,Japan,2006:510-515.
[4] 郭磊,李克强,王建强,等.用于车道识别的分段切换车道模型[J].公路交通科技,2006,23(11):90-94.
  Guo Lei,Li Keqiang,Wang Jianqiang,et al.Multi-sectional lane switch model for lane detection[J].Journal of Highway and Transportation Research and Development,2006,23(11):90-94.(in Chinese)
[5] Wang Yue,Teoh Eam Khwang,Shen Dinggang.Lane detection and tracking using B-snake[J].Image and Vision Computer,2004,22(4):269-280.
[6] Wang Yue,Shen Dinggang,Teoh Eam Khwang.Lane detection using spline model[J].Pattern Recognition Letters,2000,21(9):677-689.
[7] Su Chungyen,Fa Genhau.An effective and fast lane detection algorithm[C] //Proceedings of the 4th International Symposium on Advances in Visual Computing.Las Vegas,USA,2008,5359:942-948.
[8] Yuji Otsuka,Shoji Muramatsu.Multitype lane markers recognition using local edge direction[C] //Proceedings of IEEE Intelligent Vehicle Symposium.Versailles,France,2002,2:604-609.
[9] 陈莹,吴定会.基于全局变形模板的快速车道检测算法[J].系统仿真学报,2007,19(21):5063-5066.
  Chen Ying,Wu Dinghui.Fast lane detection using global deformable templates[J].Journal of System Simulation,2007,19(21):5063-5066.(in Chinese)
[10] Kluge Karl.Extracting road curvature and orientation from image edge points without perceptual grouping into features[C] //Proceedings of IEEE Intelligent Vehicles Symposium.Paris,France,1994:109-114.
[11] Kluge Karl,Lakshmana Sridhar.Lane boundary detection using deformable templates:effects of image subsampling on detected lane edges[C] //Proceedings of the 1995 2nd Asian Conference on Computer Vision.Singapore,1995,1035:329-339.
[12] Park S T,Yang S Y,Jung J H.Real-time lane recognition by simulated annealing algorithm [C] //Proceedings of the 4th Korea-Russia International Symposium on Science and Technology.Ulsan,Korea,2000,3:95-98.
[13] Kennedy J,Eberhart R C.A new optimizer using particles swarm theory[C] //Proceedings of the Sixth International Symposium on Micro Machine and Human Science.Nagoya,Japan,1995:109-114.
[14] Hu Xiaohui,Eberhart R C.Adaptive particle swarm optimization:detection and response to dynamic systems[C] //Proceedings of the 2002 Congress on Evolutionary Computation.Hawaii,USA,2002:1666-1670.

相似文献/References:

[1]张侃健,冯纯伯,费树岷.一类不确定非线性系统的鲁棒自适应跟踪[J].东南大学学报(自然科学版),2000,30(2):57.[doi:10.3969/j.issn.1001-0505.2000.02.012]
 Zhang Kanjian,Feng Chunbo,Fei Shumin.Robust Adaptive Tracking for Uncertain Nonlinear Systems with Unmodeled Dynamics[J].Journal of Southeast University (Natural Science Edition),2000,30(4):57.[doi:10.3969/j.issn.1001-0505.2000.02.012]
[2]黄东,宋文忠.一类递推辨识算法的评价和比较[J].东南大学学报(自然科学版),1989,19(4):90.[doi:10.3969/j.issn.1001-0505.1989.04.013]
 Huang Dong Song Wenzhong Research Institute of Automation.Evaluation and Comparison ot A Class ot Recursive Identification Algorithms[J].Journal of Southeast University (Natural Science Edition),1989,19(4):90.[doi:10.3969/j.issn.1001-0505.1989.04.013]
[3]倪受东,罗翔,文巨峰,等.冗余度机器人关节变量的滑模变结构控制研究[J].东南大学学报(自然科学版),2000,30(5):61.[doi:10.3969/j.issn.1001-0505.2000.05.014]
 Ni Shoudong,Luo Xiang,Wen Jufeng,et al.Variable Structure Control Applying in Redundant Robotics Joints Variables[J].Journal of Southeast University (Natural Science Edition),2000,30(4):61.[doi:10.3969/j.issn.1001-0505.2000.05.014]
[4]叶桦,陈海峰,陈维南.基于遗传寻优的刚体运动参数估计方法[J].东南大学学报(自然科学版),1999,29(3):101.[doi:10.3969/j.issn.1001-0505.1999.03.019]
 Ye Hua,Chen Haifen,Chen Weinan.Robust Estimation of Rigid Bodies’ Motion Parameters Based on Genetic Algorithms[J].Journal of Southeast University (Natural Science Edition),1999,29(4):101.[doi:10.3969/j.issn.1001-0505.1999.03.019]
[5]赵晓晖.耦合离散大系统分散自适应控制的稳定性[J].东南大学学报(自然科学版),1996,26(4):44.[doi:10.3969/j.issn.1001-0505.1996.04.009]
 Zhao Xiaohui.On the Stability of Discrete Time Decentralized Adaptive Control Interconnected Systems[J].Journal of Southeast University (Natural Science Edition),1996,26(4):44.[doi:10.3969/j.issn.1001-0505.1996.04.009]
[6]张天平,冯纯伯.多变量系统的鲁棒自适应控制[J].东南大学学报(自然科学版),1994,24(6):66.[doi:10.3969/j.issn.1001-0505.1994.06.012]
 Zhang Tiamping,Feng Chunbo.A Design Scheme of Robust Adaptive Control for Multivariable Systems[J].Journal of Southeast University (Natural Science Edition),1994,24(4):66.[doi:10.3969/j.issn.1001-0505.1994.06.012]
[7]费树岷,冯纯伯.模有界非线性不确定系统的鲁棒镇定[J].东南大学学报(自然科学版),1998,28(4):77.[doi:10.3969/j.issn.1001-0505.1998.04.016]
 Fei Shumin,Feng Chunbao.Nonlinear Uncertain Systems and Lyapunov Type Stabilizability[J].Journal of Southeast University (Natural Science Edition),1998,28(4):77.[doi:10.3969/j.issn.1001-0505.1998.04.016]
[8]郭晓军,程光,周爱平,等.基于扩频Manchester码的可靠自同步网络隐蔽时间通信模型[J].东南大学学报(自然科学版),2015,45(1):23.[doi:10.3969/j.issn.1001-0505.2015.01.005]
 Guo Xiaojun,Cheng Guang,Zhou Aiping,et al.Robust and self-synchronous network covert timing communication model based on spread Manchester code[J].Journal of Southeast University (Natural Science Edition),2015,45(4):23.[doi:10.3969/j.issn.1001-0505.2015.01.005]

备注/Memo

备注/Memo:
作者简介: 林国余(1979—),男,博士,讲师,Andrew.Lin@seu.edu.cn.
基金项目: 教育部博士点新教师基金资助项目(200802861061)、江苏省交通厅科技研究计划资助项目(08X09).
引文格式: 林国余,陈旭,张为公.基于多信息融合优化的鲁棒性车道检测算法[J].东南大学学报:自然科学版,2010,40(4):771-777. [doi:10.3969/j.issn.1001-0505.2010.04.021]
更新日期/Last Update: 2010-07-20