Integration of scanning and image processing algorithms for lane detection based on fuzzy method

被引：7
|
作者：
Zhang, Jindong [1 ,3 ]
Jia, Xiaoyan [2 ]
Li, Jinfeng [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Changchun 130021, Peoples R China
[2] Jilin Univ, Hosp 1, Dept Hand Surg, Changchun 130021, Peoples R China
[3] Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun, Peoples R China
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2015年 / 29卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Lane detection; fuzzy; computer vision; lane recognition; SYSTEM; IDENTIFICATION; MARKINGS; TRACKING; MACHINE;
D O I：
10.3233/IFS-151982
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to detect lane rapidly and accurately, the integration of scanning and image processing algorithms (SIP) based on the fuzzy method is proposed. Further, combination of the proposed algorithm with an adaptive threshold value for image binarization, the least-square method and Bessel curve algorithm are proposed for detection and to fit the lane. The proposed SIP algorithm was evaluated by various tests. The experimental results indicate that the average time consumed for the detection of lane in each frame is 16.7639 ms, and the accuracy of lane detection is 95%. The proposed algorithm demonstrates good robustness, and can be used as the core algorithm for further application in lane departure warning systems.
引用
收藏
页码：2779 / 2786
页数：8
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