Lane detection using histogram-based segmentation and decision trees

Author

González, Juan Pablo ; Özgüner, Ümit

Author_Institution

Gen. Dynamics Robotic Syst., Westminster, MD, USA

fYear

2000

fDate

2000

Firstpage

346

Lastpage

351

Abstract

A vision system for intelligent vehicles is proposed here. The system exploits the characteristics of the gray level histogram of the road to detect lane markers. Each lane marker is then analyzed using a decision tree, and finally the relations between lane markers are analyzed to create structures defining the lane boundaries. The resulting system also generates images that can be used as preprocessing stages in lane detection, lane tracking or obstacle detection algorithms. The system runs in realtime at rates of about 30 Hz

Keywords

computer vision; decision trees; image recognition; image segmentation; road vehicles; 30 Hz; decision tree; decision trees; gray level histogram; histogram-based segmentation; intelligent vehicles; lane boundaries; lane detection; lane marker detection; lane tracking; obstacle detection algorithms; preprocessing stages; vision system; Classification tree analysis; Decision trees; Geometry; Image segmentation; Intelligent robots; Intelligent vehicles; Layout; Road vehicles; Robot vision systems; Vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Transportation Systems, 2000. Proceedings. 2000 IEEE

Conference_Location

Dearborn, MI

Print_ISBN

0-7803-5971-2

Type

conf

DOI

10.1109/ITSC.2000.881084

Filename

881084