Title :
Robust course-boundary extraction algorithms for autonomous vehicles
Author :
Roman, Chris ; Reinholtz, Charles
Author_Institution :
Structural Syst. & Control Group, California Univ., San Diego, La Jolla, CA, USA
Abstract :
Practical autonomous robotic vehicles require dependable methods for accurately identifying course or roadway boundaries. The authors have developed a method to reliably extract the boundary line using simple dynamic thresholding, noise filtering, and blob removal. This article describes their efforts to apply this procedure in developing an autonomous vehicle
Keywords :
computer vision; driver information systems; autonomous robotic vehicles; autonomous vehicles; blob removal; boundary line extraction; dynamic thresholding; noise filtering; robust course-boundary extraction algorithms; Asphalt; Charge coupled devices; Hardware; Machine vision; Mobile robots; Navigation; Power system reliability; Remotely operated vehicles; Robustness; Signal processing algorithms;
Journal_Title :
Intelligent Systems and their Applications, IEEE
DOI :
10.1109/5254.736000
