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Real-time lane detection on suburban streets using visual cue integration

Fernando, Shehan, Udawatta, Lanka, Horan, Ben and Pathirana, Pubudu 2014, Real-time lane detection on suburban streets using visual cue integration, International journal of advanced robotic systems, vol. 11, no. 4, pp. 1-20, doi: 10.5772/58248.

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Title Real-time lane detection on suburban streets using visual cue integration
Author(s) Fernando, Shehan
Udawatta, Lanka
Horan, BenORCID iD for Horan, Ben orcid.org/0000-0002-6723-259X
Pathirana, PubuduORCID iD for Pathirana, Pubudu orcid.org/0000-0001-8014-7798
Journal name International journal of advanced robotic systems
Volume number 11
Issue number 4
Start page 1
End page 20
Total pages 20
Publisher InTech
Place of publication Rijeka, Croatia
Publication date 2014-04-14
ISSN 1729-8814
1729-8806
Keyword(s) Entropy measure
Gabor filter
Mahalanobis distance
Studentized residuals
Visual cue integration
Summary The detection of lane boundaries on suburban streets using images obtained from video constitutes a challenging task. This is mainly due to the difficulties associated with estimating the complex geometric structure of lane boundaries, the quality of lane markings as a result of wear, occlusions by traffic, and shadows caused by road-side trees and structures. Most of the existing techniques for lane boundary detection employ a single visual cue and will only work under certain conditions and where there are clear lane markings. Also, better results are achieved when there are no other onroad objects present. This paper extends our previous work and discusses a novel lane boundary detection algorithm specifically addressing the abovementioned issues through the integration of two visual cues. The first visual cue is based on stripe-like features found on lane lines extracted using a two-dimensional symmetric Gabor filter. The second visual cue is based on a texture characteristic determined using the entropy measure of the predefined neighbourhood around a lane boundary line. The visual cues are then integrated using a rulebased classifier which incorporates a modified sequential covering algorithm to improve robustness. To separate lane boundary lines from other similar features, a road mask is generated using road chromaticity values estimated from CIE L*a*b* colour transformation. Extraneous points around lane boundary lines are then removed by an outlier removal procedure based on studentized residuals. The lane boundary lines are then modelled with Bezier spline curves. To validate the algorithm, extensive experimental evaluation was carried out on suburban streets and the results are presented. 
Language eng
DOI 10.5772/58248
Field of Research 090602 Control Systems, Robotics and Automation
Socio Economic Objective 810103 Command, Control and Communications
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2014, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30065824

Document type: Journal Article
Collections: School of Engineering
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.