RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions

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 ca...

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Main Authors: Lim, Hann, Seng, K., Ang, L.
Format: Conference Paper
Published: 2010
Online Access:http://hdl.handle.net/20.500.11937/12190
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author Lim, Hann
Seng, K.
Ang, L.
author_facet Lim, Hann
Seng, K.
Ang, L.
author_sort Lim, Hann
building Curtin Institutional Repository
collection Online Access
description 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. © 2010 IEEE.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T06:58:13Z
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spelling curtin-20.500.11937-121902017-09-13T14:56:51Z RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions Lim, Hann Seng, K. Ang, L. The application of edge detection to obtain salient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. © 2010 IEEE. 2010 Conference Paper http://hdl.handle.net/20.500.11937/12190 10.1109/ICCSIT.2010.5565151 restricted
spellingShingle Lim, Hann
Seng, K.
Ang, L.
RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions
title RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions
title_full RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions
title_fullStr RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions
title_full_unstemmed RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions
title_short RETRACTED ARTICLE: Improvement of lane marks extraction technique under different road conditions
title_sort retracted article: improvement of lane marks extraction technique under different road conditions
url http://hdl.handle.net/20.500.11937/12190