dc.contributor.author |
Jiang, Ruyi |
en |
dc.contributor.author |
Klette, Reinhard |
en |
dc.contributor.author |
Wang, Shigang |
en |
dc.contributor.author |
Vaudrey, Tobi |
en |
dc.date.accessioned |
2009-06-16T01:07:38Z |
en |
dc.date.available |
2009-06-16T01:07:38Z |
en |
dc.date.issued |
2009 |
en |
dc.identifier.citation |
Multimedia Imaging Report 42 (2009) |
en |
dc.identifier.issn |
1178-5789 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/4357 |
en |
dc.description |
You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the original MI_tech website http://www.mi.auckland.ac.nz/index.php?option=com_content&view=article&id=127&Itemid=113 . All other rights are reserved by the author(s). |
en |
dc.description.abstract |
Lane detection and tracking is a significant component of vision-based
driver assistance systems (DAS). Low-level image processing is the first step in
such a component. This paper suggests three useful techniques for low-level image
processing in lane detection situations: bird’s-eye view mapping, a specialized
edge detection method, and the distance transform. The first two techniques
have been widely used in DAS, while the distance transform is a method newly
exploited in DAS, that can provide useful information in lane detection situations.
This paper recalls two methods to generate a bird’s-eye image from the
original input image, it also compares edge detectors. A modified version of the
Euclidean distance transform called real orientation distance transform (RODT)
is proposed. Finally, the paper discusses experiments on lane detection and tracking
using these technologies. |
en |
dc.publisher |
Computer Science Department, The University of Auckland, New Zealand |
en |
dc.relation.ispartofseries |
MI-tech Report Series |
en |
dc.rights |
Copyright Computer Science Department, The University of Auckland. You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the original CITR web site under terms that include this permission. All other rights are reserved by the author(s). |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.source.uri |
http://www.mi.auckland.ac.nz/tech-reports/MItech-TR-42.pdf |
en |
dc.title |
Low-level Image Processing for Lane Detection and Tracking |
en |
dc.type |
Technical Report |
en |
dc.subject.marsden |
Fields of Research::280000 Information, Computing and Communication Sciences |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |