Title :
Road Markers Recognition Based on Shape Information
Author :
Li, Yunchong ; He, Kezhong ; Jia, Peifa
Author_Institution :
Tsinghua Univ., Beijing
Abstract :
Road information understanding is a necessary task for intelligent vehicles and driver assistance systems. Previous research mostly focused on the detection and estimation of lane position. Other information provided by road markers was scarcely mentioned. We propose a shape-based road marker detection and recognition method in this paper. The 8-neighbor chain codes of close regions are abstracted from the plane image. Selected moment features and an improved minimal-error-rate classifier are utilized to recognized different lane markers and other road markers. The lengths and slopes of lane markers are fast calculated also using the moment features. The results show that the method can detect and recognize road markers effectively.
Keywords :
automated highways; image classification; driver assistance systems; intelligent vehicles; minimal-error-rate classifier; road information; shape information; shape-based road marker detection; shape-based road marker recognition; Cameras; Helium; Image generation; Intelligent systems; Intelligent vehicles; Laboratories; Pattern matching; Roads; Shape; Vehicle detection;
Conference_Titel :
Intelligent Vehicles Symposium, 2007 IEEE
Conference_Location :
Istanbul
Print_ISBN :
1-4244-1067-3
Electronic_ISBN :
1931-0587
DOI :
10.1109/IVS.2007.4290101