Cited 0 time in webofscience Cited 0 time in scopus

Multi-Lane Dection and Tracking using Dual Parabolic Model

Title
Multi-Lane Dection and Tracking using Dual Parabolic Model
Authors
Kwon, SoonDing, Da JunYu, Jong SuJung, Je KyoJin, Sung Ho
DGIST Authors
Kwon, Soon; Ding, Da Jun; Yu, Jong Su; Jung, Je Kyo; Jin, Sung Ho
Issue Date
2015-01
Citation
Bulletin of Networking, Computing, Systems, and Software, 4(1), 65-68
Type
Article
ISSN
2186-5140
Abstract
Multi-lane recognition system gives a significant assistance for driver’s safety. In this paper, we try to use a dual parabolic model for more precious and robust lane description. For gathering an efficient feature, we used a parallel RANSAC algorithm. The line model characterization is combined with adjacent point histogram peak analysis and two-axis parabola. Proposed algorithm can detect lane automatically and adaptively in every frame. The designed method is applied using various video images captured from the commercial black box camera and is verified to be robust.
URI
http://hdl.handle.net/20.500.11750/13340
Publisher
Science & Engineering Research Support soCiety
Related Researcher
  • Author Kwon, Soon  
  • Research Interests computer vision; deep learning; autonomous driving; parallel processing; vision system on chip
Files:
There are no files associated with this item.
Collection:
Division of Automotive Technology1. Journal Articles


qrcode mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE