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Author:

Tian, Jingyi (Tian, Jingyi.) | Wang, Zhiqiang (Wang, Zhiqiang.) | Zhu, Qing (Zhu, Qing.)

Indexed by:

EI Scopus

Abstract:

In modern society, with the economic conditions getting better, more and more vehicles are produced. So many vehicles bring about the rapid development of traffic transportation and the traffic accidents happen frequently. With the fast development of computer technology, more and more interests are focused on vision navigation technology in Intelligent Vehicle System. At the same time, lane detection is an important component of intelligent vehicle vision navigation system. In order to improve the real-time detection, an improved lane boundaries detection based on dynamic regions of interest is presented. The approach is an essential tasking both autonomous lane vehicles research and active safety system development. Lane detection is, however, still a challenging issue due to the complexity of the real road scenes. Our approach takes advantage of the image preprocessing with different processing on the images with different illumination, ROI decision algorithm and lane detection based on the vanishing point and Hough transform. The achieved results reveal that the Hough transform with the dynamic ROI algorithm and vanishing point method is more effective. © 2017 IEEE.

Keyword:

Intelligent vehicle highway systems Feature extraction Vehicles Hough transforms Navigation systems Active safety systems Accidents

Author Community:

  • [ 1 ] [Tian, Jingyi]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Wang, Zhiqiang]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Zhu, Qing]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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Source :

Year: 2017

Volume: 2017-January

Page: 1212-1217

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

Online/Total:1016/10532276
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