Dynamic integration and online evaluation of vision-based lane detection algorithms
Lane detection techniques have been widely studied in the last two decades and applied in many advance driver assistance systems. However, the development of a robust lane detection system, which can deal with various road conditions and efficiently evaluate its detection results in real time, is st...
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| Vydáno v: | IET intelligent transport systems Ročník 13; číslo 1; s. 55 - 62 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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The Institution of Engineering and Technology
01.01.2019
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| ISSN: | 1751-956X, 1751-9578 |
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| Abstract | Lane detection techniques have been widely studied in the last two decades and applied in many advance driver assistance systems. However, the development of a robust lane detection system, which can deal with various road conditions and efficiently evaluate its detection results in real time, is still of great challenge. In this study, a vision-based lane detection system with dynamic integration and online evaluation is proposed. To increase the robustness of the lane detection system, the integration system dynamically processes two lane detection modules. First, a primary lane detection module is designed based on the steerable filter and Hough transform algorithm. Then, a secondary algorithm, which combines the Gaussian mixture model for image segmentation and random sample consensus for lane model fitting, will be activated when the primary algorithm encounters a low detection confidence. To detect the colour and line style of the ego lanes and evaluate the lane detection system in real time, a lane sampling and voting technique is proposed. By combining the sampling and voting system system with prior lane geometry knowledge, the evaluation system can efficiently recognise the false detections. The system works robustly in various complex situations (e.g. shadows, night, and lane missing scenarios) with a monocular camera. |
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| AbstractList | Lane detection techniques have been widely studied in the last two decades and applied in many advance driver assistance systems. However, the development of a robust lane detection system, which can deal with various road conditions and efficiently evaluate its detection results in real time, is still of great challenge. In this study, a vision-based lane detection system with dynamic integration and online evaluation is proposed. To increase the robustness of the lane detection system, the integration system dynamically processes two lane detection modules. First, a primary lane detection module is designed based on the steerable filter and Hough transform algorithm. Then, a secondary algorithm, which combines the Gaussian mixture model for image segmentation and random sample consensus for lane model fitting, will be activated when the primary algorithm encounters a low detection confidence. To detect the colour and line style of the ego lanes and evaluate the lane detection system in real time, a lane sampling and voting technique is proposed. By combining the sampling and voting system system with prior lane geometry knowledge, the evaluation system can efficiently recognise the false detections. The system works robustly in various complex situations (e.g. shadows, night, and lane missing scenarios) with a monocular camera. |
| Author | Velenis, Efstathios Cao, Dongpu Xing, Yang Wang, Huaji Lv, Chen |
| Author_xml | – sequence: 1 givenname: Yang surname: Xing fullname: Xing, Yang organization: 1Advanced Vehicle Engineering Centre, Cranfield University, Cranfield, UK – sequence: 2 givenname: Chen surname: Lv fullname: Lv, Chen organization: 2School of Mechanical and Aerospace Engineering Nanyang Technological University, 639798, Singapore – sequence: 3 givenname: Huaji surname: Wang fullname: Wang, Huaji organization: 3AVL Powertrain UK Ltd, Coventry, CV4 7EZ, UK – sequence: 4 givenname: Dongpu surname: Cao fullname: Cao, Dongpu email: dongpu.cao@uwaterloo.ca organization: 4Department of Mechanical and Mechatronics Engineering, University of Waterloo, N2L 3G1, Canada – sequence: 5 givenname: Efstathios surname: Velenis fullname: Velenis, Efstathios organization: 1Advanced Vehicle Engineering Centre, Cranfield University, Cranfield, UK |
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| Cites_doi | 10.1109/TITS.2013.2246835 10.1145/358669.358692 10.1155/2012/465819 10.1016/0031-3203(81)90009-1 10.1016/j.neunet.2016.12.002 10.1109/VPPC.2015.7352903 10.1109/IVS.2008.4621152 10.1109/TVT.2013.2242910 10.1109/TVT.2013.2281199 10.1177/1687814015593866 10.1109/ITSC.2013.6728473 10.1109/TVT.2016.2582721 10.1109/TMECH.2016.2631897 10.1080/00423114.2014.938663 10.1109/CIMSim.2012.31 10.1109/TITS.2015.2492019 10.1109/TMECH.2016.2533635 10.1109/TITS.2015.2438714 10.1007/s00138-011-0404-2 10.1016/j.imavis.2003.10.003 10.1007/s10514-009-9113-3 10.1109/34.93808 10.1016/j.patcog.2014.10.011 10.1109/TITS.2014.2321108 10.1109/IPTA.2015.7367103 10.1109/TVT.2016.2555853 10.1162/neco.1996.8.1.129 10.1109/TITS.2006.869595 10.1109/ICPR.2014.453 |
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| Keywords | Hough transform algorithm dynamic integration advance driver assistance systems steerable filter false detections integration system object detection vision-based lane detection algorithms SVT system Gaussian mixture model cameras robust lane detection system ego lanes lane missing scenarios road vehicles feature extraction image segmentation edge detection real time low detection confidence traffic engineering computing voting technique online evaluation Hough transforms computer vision Gaussian processes lane sampling lane geometry knowledge primary lane detection module |
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| Snippet | Lane detection techniques have been widely studied in the last two decades and applied in many advance driver assistance systems. However, the development of a... |
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| SubjectTerms | advance driver assistance systems cameras computer vision dynamic integration edge detection ego lanes false detections feature extraction Gaussian mixture model Gaussian processes Hough transform algorithm Hough transforms image segmentation integration system lane geometry knowledge lane missing scenarios lane sampling low detection confidence object detection online evaluation primary lane detection module real time road vehicles robust lane detection system Special Issue: Recent Advancements on Electrified, Low Emission and Intelligent Vehicle-Systems steerable filter SVT system traffic engineering computing vision‐based lane detection algorithms voting technique |
| Title | Dynamic integration and online evaluation of vision-based lane detection algorithms |
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