Lane Detection Based on Machine Learning Algorithm

Chao Fan, Jingbo Xu, Shuai Di

Abstract


In order to improve accuracy and robustness of the lane detection in complex conditions, such as the shadows and illumination changing, a novel detection algorithm was proposed based on machine learning. After pretreatment, a set of haar-like filters were used to calculate the eigenvalue in the gray image f(x,y) and edge e(x,y). Then these features were trained by using improved boosting algorithm and the final class function g(x) was obtained, which was used to judge whether the point x belonging to the lane or not. To avoid the over fitting in traditional boosting, Fisher discriminant analysis was used to initialize the weights of samples. After testing by many road in all conditions, it showed that this algorithm had good robustness and real-time to recognize the lane in all challenging conditions.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3923

 


Keywords


lane detection; machine learning; haar-like; improved boosting algorithm

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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