An Intelligent Vehicle Robust Lane Line Identification Method Based on Machine Vision

被引：2
|
作者：
Li M. [1 ]
Lyu H. [1 ]
Wang F. [1 ]
Jia D. [1 ]
机构：
[1] School of Mechanical and Power Engineering, Harbin, University of Science and Technology, Harbin
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2021年 / 32卷 / 02期
关键词：
Feature detection; Intelligent vehicle; Lane line identification; Machine vision; Robustness;
D O I：
10.3969/j.issn.1004-132X.2021.02.016
中图分类号：
学科分类号：
摘要：
A robust lane recognition method for intelligent vehicles was proposed based on machine vision herein to solve the problem that the traditional lane recognition algorithm was difficult to recognize in the complex road environments. Firstly, in order to eliminate noise interference and improve the efficiency of feature detection, an adaptive region of interest (ROI) calculation method was designed, which could adaptively separate the lane region from the non lane region according to different conditions. Secondly, to improve the environmental adaptability of the algorithm, the detection operator of improved partition angle was used to detect the lane line features, and the multi-color threshold processing was used to deal with the lane images. Finally, DBSCAN clustering and NURBS curve were used to fit the lane line after changing the view angle, and random sampling consistency method was used to optimize the lane line model to filter out mismatches. Experimental results show that the algorithm may effectively identify lane lines under various road conditions. © 2021, China Mechanical Engineering Magazine Office. All right reserved.
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页码：242 / 251
页数：9
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