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Knowledge on road information in sub-urban lane detection via multiple cue integration
conference contribution
posted on 2010-01-01, 00:00 authored by L Udawatta, S Fernando, Pubudu PathiranaPubudu PathiranaDetection 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.
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Event
ICT and Knowledge Engineering. Conference (8th : 2010 , Bangkok, Thailand)Pagination
64 - 69Publisher
IEEELocation
Bangkok, ThailandPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2010-11-24End date
2010-11-25ISSN
2157-0981ISBN-13
9781424498758Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2010, IEEETitle of proceedings
ICT and KE 2010 : Proceedings of the 8th International Conference on ICT and Knowledge EngineeringUsage metrics
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