Ren, FeixiangHuang, JinshengJiang, RuyiKlette, Reinhard2009-06-162009-06-162009Multimedia Imaging Report 43 (2009)1178-5789http://hdl.handle.net/2292/4358You 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).A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, play station, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.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).https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htmLane Detection on the iPhoneTechnical ReportFields of Research::280000 Information, Computing and Communication Scienceshttp://purl.org/eprint/accessRights/OpenAccess