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Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The application of edge detection to obtain salient lane boundaries on road image is popular in the computer vision area. However, edge detectors may be easily distracted by manifold noises that emerged on the road surface such as shadow cast, vehicles or other obstacles. Additionally, sky region can adversely affect the performance of lane detection method due to the presence of horizontal edges in the sky region. In this paper, lane preprocessing approach is proposed to effectively extract lane marks from the traffic scene. Horizon localization is improved to automatically segment the sky and road region through regional minimum search. It is followed by the lane region analysis to adaptively remove the road pixels and obstacles. Evaluations on the proposed lane preprocessing method are performed under different time of the day/night and various road sceneries such as city, highway, rural, suburban etc. Some results and findings are shown in the paper with regards on the observation of the road intensity change respective to the variation of the road conditions.