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

Udawatta, Lanka, Fernando, Shehan and Pathirana, Pubudu N. 2010, Knowledge on road information in sub-urban lane detection via multiple cue integration, in ICT and KE 2010 : Proceedings of the 8th International Conference on ICT and Knowledge Engineering, IEEE, Piscataway, N.J., pp. 64-69.

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Title Knowledge on road information in sub-urban lane detection via multiple cue integration
Author(s) Udawatta, Lanka
Fernando, Shehan
Pathirana, Pubudu N.
Conference name ICT and Knowledge Engineering. Conference (8th : 2010 , Bangkok, Thailand)
Conference location Bangkok, Thailand
Conference dates 24-25 Nov. 2010
Title of proceedings ICT and KE 2010 : Proceedings of the 8th International Conference on ICT and Knowledge Engineering
Editor(s) [Unknown]
Publication date 2010
Conference series ICT and Knowledge Engineering Conference
Start page 64
End page 69
Total pages 110 p.
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Mahalanobis distance
entropy measure
morphological operations
Gabor filter
studentized residuals
Bezier splines
Summary 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.
ISBN 9781424498758
ISSN 2157-0981
Language eng
Field of Research 090602 Control Systems, Robotics and Automation
Socio Economic Objective 810103 Command, Control and Communications
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2010
Copyright notice ©2010, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30033805

Document type: Conference Paper
Collection: School of Engineering
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