Road detection is one of the most important research areas in driver assistance and automated driving field. However, the performance of existing methods is still unsatisfactory, especially in severe shadow conditions. To overcome those difficulties, first we propose a novel shadow-free feature extractor based on the color distribution of road surface pixels. Then we present a road detection framework based on the extractor, whose performance is more accurate and robust than that of existing extractors. Also, the proposed framework has much low-complexity, which is suitable for usage in practical systems. 

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@inproceedings{ying2016novel,
  title={A Novel Shadow-Free Feature Extractor for Real-Time Road Detection},
  author={Ying, Zhenqiang and Li, Ge and Zang, Xianghao and Wang, Ronggang and Wang, Wenmin},
  booktitle={Proceedings of the 2016 ACM on Multimedia Conference},
  pages={611--615},
  year={2016},
  organization={ACM}
}