By Topic

Knowlege on road information in sub-urban lane detection via multiple cue integration

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Lanka Udawatta ; Department of Engineering, University of Moratuwa, Katubedda, Sri Lanka ; Shehan Fernando ; Pubudu N. Pathirana

Detection of lane boundaries of a road based on the images or video taken by a video capturing device in a suburban environment is a challenging task. In this paper, a novel lane detection algorithm is proposed without considering camera parameters; which robustly detects lane boundaries in real-time especially for sub-urban roads. Initially, the proposed method fits the CIE L*a* b* transformed road chromaticity values (that is a* and b* values) to a bi-variate Gaussian model followed by the classification of road area based on Mahalanobis distance. Secondly, the classified road area acts as an arbitrary shaped region of interest (AROI) in order to extract blobs resulting from the filtered image by a two dimensional Gabor filter. This is considered as the first cue of images. Thirdly, another cue of images was employed in order to obtain an entropy image. Moreover, results from the color based image cue and entropy image cue were integrated following an outlier removing process. Finally, the correct road lane points are fitted with Bezier splines which act as control points that can form arbitrary shapes. The algorithm was implemented and experiments were carried out on sub-urban roads. The results show the effectiveness of the algorithm in producing more accurate lane boundaries on curvatures and other objects on the road.

Published in:

2010 Eighth International Conference on ICT and Knowledge Engineering

Date of Conference:

24-25 Nov. 2010