DESIGN OF A COMPUTER STEREO VISION BASED ROAD MARKING SYSTEM

被引：0

作者：

Suryakant ^{[1
]}

Kumar, Amod ^{[1
]}

Saini, Garima ^{[1
]}

机构：

[1] NITTTR, ECE, Chandigarh, India

来源：

2022 IEEE INTERNATIONAL IOT, ELECTRONICS AND MECHATRONICS CONFERENCE (IEMTRONICS) | 2022年

关键词：

Road markings; stereo vision; disparity map; semi-global matching; computer vision; image processing; automation;

D O I：

10.1109/IEMTRONICS55184.2022.9795778

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Existing methods to put white and yellow marking on the road are based on manual measurement of the road dimensions and manual marking of guide lines. It is a time consuming, cumbersome and labour intensive process. This was the motivation for this work to develop a system which can automatically apply road markings according to the width of the road. In this paper, a stereo-vision based road marking system is presented. Computer stereo-vision has been used to measure the width of the road which helps us decide the number of lanes on the road. To generate the disparity map, a semi-global matching algorithm has been used, incorporating the advantages of both local and global matching algorithms. Efficient algorithms have been used for camera calibration and to estimate the road width. For deciding the number of lanes, the standards laid down by Indian Road Congress (IRC) have been followed..

引用

页码：819 / 824

页数：6

共 50 条

[31] Stereo vision-based road estimation assisted by efficient planar patch calculation [J].

Ozgunalp, U. ;

Ai, X. ;

Dahnoun, N. .

SIGNAL IMAGE AND VIDEO PROCESSING, 2016, 10 (06) :1127-1134

[32] Stereo vision-based road estimation assisted by efficient planar patch calculation [J].

U. Ozgunalp ;

X. Ai ;

N. Dahnoun .

Signal, Image and Video Processing, 2016, 10 :1127-1134

[33] Stereo Vision-Based Obstacle Detection Using Fusion Method of Road Scenes [J].

Ding, Dajun ;

Kwon, Soon ;

Park, Jaehyeong ;

Jung, Wooyoung .

TENCON 2015 - 2015 IEEE REGION 10 CONFERENCE, 2015,

[34] Monocular Vision based Road Marking Recognition for Driver Assistance and Safety [J].

Sukhwani, Mohak ;

Singh, Suriya ;

Goyal, Anirudh ;

Behl, Aseem ;

Mohapatra, Pritish ;

Bharti, Brijendra Kumar ;

Jawahar, C. V. .

2014 IEEE INTERNATIONAL CONFERENCE ON VEHICULAR ELECTRONICS AND SAFETY (ICVES), 2014, :11-16

[35] Self calibration of a road stereo vision system through correlation criterions [J].

Kramm, Sebastien ;

Miche, Pierre ;

Bensrhair, Abdelaziz .

2006 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 2006, :36-+

[36] Binocular stereo vision system design for lunar rover [J].

Chu, Jun ;

Jiao, Chunlin ;

Guo, Hang ;

Zhang, Xiaoyu .

MIPPR 2007: PATTERN RECOGNITION AND COMPUTER VISION, 2007, 6788

[37] Telerobot Control System Based on Stereo Vision [J].

Kim, Jong Whan ;

Kang, Jeong Seok ;

Park, Hong Seong .

2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAL), 2012, :114-115

[38] Model based design of a stereo vision system for intelligent deep-sea operations [J].

Luczynski, Tomasz ;

Luczynski, Piotr ;

Pehle, Lukas ;

Wirsum, Manfred ;

Birk, Andreas .

MEASUREMENT, 2019, 144 :298-310

[39] Design of Intelligent Aim System of Tear Bomb Emitter Based on Binocular Stereo Vision [J].

Jie, Zhang .

MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5, 2012, 130-134 :3505-3510

[40] Design of fruit harvesting robot based on stereo vision [J].

Zhou J. ;

Liu R. ;

Zhang G. .

Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery, 2010, 41 (06) :158-162

← 1 2 3 4 5 →