Lane Detection on the iPhone

  • Feixiang Ren
  • Jinsheng Huang
  • Mutsuhiro Terauchi
  • Ruyi Jiang
  • Reinhard Klette
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 30)


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, PlayStation, 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.


Intelligent transportation system driver assistance lane detection iPhone Hough transform 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
  2. 2.
    Duda, R.O., Hart, P.E.: Use of the Hough transformation to detect lines and curves in pictures. Comm. ACM 15, 11–15 (1972)CrossRefzbMATHGoogle Scholar
  3. 3.
  4. 4.
    iPhone: official website by Apple,
  5. 5.
    Jiang, R., Klette, R., Wang, S., Vaudrey, T.: Lane detection and tracking using a new lane model and distance transform. Technical report, MItech-TR-39, The University of Auckland (2009)Google Scholar
  6. 6.
    Kim, Z.: Realtime lane tracking of curved local roads. In: Proc. IEEE Conf. Intelligent Transportation Systems, pp. 1149–1155 (2006)Google Scholar
  7. 7.
    John, B.M.: Application of the Hough transform to lane detection and following on high speed roads. In: Proc. Irish Signals and Systems Conference (2001)Google Scholar
  8. 8.
    Kim, Z.: Robust lane detection and tracking in challenging scenarios. IEEE Trans. Intelligent Transportation Systems 9, 16–26 (2008)CrossRefGoogle Scholar
  9. 9.
    McCall, J., Trivedi, M.M.: Video based lane estimation and tracking for driver assistance: Survey, algorithms, and evaluation. IEEE Trans. Intelligent Transportation Systems 7, 20–37 (2006)CrossRefGoogle Scholar
  10. 10.
    Wang, Y., Teoh, E., Shen, D.: Lane detection and tracking using B-snake. Image Vision Computing 22, 269–280 (2004)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2010

Authors and Affiliations

  • Feixiang Ren
    • 1
  • Jinsheng Huang
    • 1
  • Mutsuhiro Terauchi
    • 2
  • Ruyi Jiang
    • 3
  • Reinhard Klette
    • 1
  1. 1.The University of AucklandAucklandNew Zealand
  2. 2.Hiroshima International UniversityHiroshimaJapan
  3. 3.Shanghai Jiao Tong UniversityShanghaiChina

Personalised recommendations