A traffic image semantic segmentation algorithm based on UNET

Abstract

In recent years, the traffic image semantic segmentation plays a crucial role in automatic driving. The result of semantic segmentation will directly affect the car's understanding of the external scene. Thus, a semantic segmentation algorithm based on UNET network model is proposed for getting better results in traffic images segmentation. To prove the effectiveness of the proposed algorithm, highway driving dataset is used on the experiments. The experimental results show that the proposed network can achieve high precision image semantic segmentation in complex road scenes, and the segmentation accuracy is greatly improved compared with other network models.