Publication:
Adaptative road lanes detection and classification

Thumbnail Image
Identifiers
URI: https://hdl.handle.net/10016/7108
ISSN: 0302-9743 (Print)
ISSN: 1611-3349 (Online)
ISBN: 978-3-540-44630-9
DOI: 10.1007/11864349_105
Files
adaptative_collado_ACIVS_2006_ps.pdf (1.08 MB)
Publication date
2006-10
Defense date
Authors
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
This paper presents a Road Detection and Classification algorithm for Driver Assistance Systems (DAS), which tracks several road lanes and identifies the type of lane boundaries. The algorithm uses an edge filter to extract the longitudinal road markings to which a straight lane model is fitted. Next, the type of right and left lane boundaries (continuous, broken or merge line) is identified using a Fourier analysis. Adjacent lanes are searched when broken or merge lines are detected. Although the knowledge of the line type is essential for a robust DAS, it has been seldom considered in previous works. This knowledge helps to guide the search for other lanes, and it is the basis to identify the type of road (one-way, two-way or freeway), as well as to tell the difference between allowed and forbidden maneuvers, such as crossing a continuous line.
Description
Proceeding of: 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006
Keywords
Bibliographic citation
Advanced concepts for intelligent vision systems : 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006. Proceedings. Springer, 2006, p. 1151-1162
Collections
DISA - LSI - Artículos en Congresos Internacionales