Robust lane marking detection based on multi-feature fusion
- Format
- Article
- Status
- publishedVersion
- Description
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.
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.
- Publication Year
- 2018
- Language
- eng
- Topic
- Image color analysis
Feature extraction
Roads
Image edge detection
Cameras
Vehicles
Image segmentation
Image color analysis
Feature extraction
Roads
Image edge detection
Cameras
Vehicles
Image segmentation
- Repository
- RI de Documento Digitales de Acceso Abierto de la UTP
- Get full text
- https://ieeexplore.ieee.org/abstract/document/7529668/
http://ridda2.utp.ac.pa/handle/123456789/5095
- Rights
- embargoedAccess
- License