Title :
Detection and classification of road lanes with a frequency analysis
Author :
Collado, J.M. ; Hilario, Cristina ; de la Escalera, A. ; Armingol, Jose M.
Author_Institution :
Dept. of Intelligent Syst. & Autom., Univ. Carlos III de Madrid, Spain
Abstract :
This paper presents a road lane detection and interpretation algorithm for driver assistance systems (DAS). The algorithm uses an edge filter to extract lane borders to which a straight lane model is fitted. Next, the lane mark type (continuous, discontinuous or merge) is recognized using a Fourier analysis. The line type is essential for a robust DAS. Nevertheless, it has been seldom considered in previous works. The knowledge of the line types of the road helps to guide the search for other lines, to automatically detect the type of the road (one-way, two way or highway), and to tell the difference between allowed and forbidden maneuvers, such as crossing a continuous line. Furthermore, the system is able to auto calibrate, thus easing the process of installation in commercial vehicles.
Keywords :
Fourier analysis; automated highways; computer vision; driver information systems; feature extraction; image classification; object detection; road vehicles; Fourier analysis; auto calibration; driver assistance system; edge filter; frequency analysis; image processing; intelligent transportation system; machine vision; object detection; road lane classification; road lane detection; road vehicle; Automated highways; Cameras; Frequency; Intelligent transportation systems; Intelligent vehicles; Machine intelligence; Object detection; Road transportation; Road vehicles; Vehicle detection;
Conference_Titel :
Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
Print_ISBN :
0-7803-8961-1
DOI :
10.1109/IVS.2005.1505081