Robust lane marking detection based on multi-feature fusion
In the field of intelligent vehicle systems (IVS), color and edge of lane markings are important features for vision-based applications. This paper proposes a method to detect lane marking based on a fusion approach which combine color and edge lane marking information. Firstly, by knowing the vehic...
| Autores Principales: | Cáceres Hernández, Danilo, Seo, Dongwook, Hyun Jo, Kang |
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| Formato: | Artículo |
| Idioma: | Inglés |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: |
https://ieeexplore.ieee.org/abstract/document/7529668/ http://ridda2.utp.ac.pa/handle/123456789/5095 http://ridda2.utp.ac.pa/handle/123456789/5095 |
| Sumario: |
In the field of intelligent vehicle systems (IVS), color and edge of lane markings are important features for vision-based applications. This paper proposes a method to detect lane marking based on a fusion approach which combine color and edge lane marking information. Firstly, by knowing the vehicle speed the road surface region of interest is extracted using the typical stopping distance. Secondly, a lane marking clustering method is introduced. This is done by combining the edge and color information of the lane marking. Finally, a fitting model is implemented. A line fitting model is used to extract the lane marking parameters. However for those regions in which lane can not described as a line, the algorithm computed the curve parameters using Lagrange interpolating polynomial. |
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