关键词: 自然场景文字检测, 深度学习, 全卷积网络, 语义分割

Abstract: The traditional natural scene text detection method using some handcraft features always lacks robustness in dealing with complex natural scenes. A novel text detection method based on the deep learning is proposed, which aims at sloving the problem of multi-directional text detection in the complex natural scenes. Firstly, this paper uses Fully Convolutional Networks（FCN） and fuses the multi-scale feature map, it combines semantic segmentation to divide text candidate regions. Secondly, the text candidate detection boxes are obtained through the text candidate regions directly and then it enlarges compensation treatment. Finally, the text detection results are obtained after some post-processings. The proposed method has been evaluated on the ICDAR2013 and the ICDAR2015 standard datasets, and the experimental results show that this method has achieved better performance compared with some state of the art methods.

Key words: natural scene text detection, deep learning, Fully Convolutional Networks（FCN）, semantic segmentation