Semantic segmentation is a technique for classifying images pixel by pixel. The road surface cracks are difficult to extract with traditional method because they are exposed to more environmental factors such as light and more interference noise. This paper proposes a road surface crack detection technology based on RU-Net. The impact of environmental factors is effectively reduced by this network, and it realizes the classification of cracks from end to end and pixel by pixel. The network mainly includes two parts which are encoder and decoder. The encoder part is mainly used for feature extraction, and the decoder part is mainly used to recover spatial information. The results of the experiment show that the RU-Net achieves an accuracy of more than 98% and an MIoU of more than 73%.
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