Abstract
Detection of text in natural scene images is very challenging, and it is not completely solved. In this work we propose a fast and reliable algorithm to generate synthetic data of Chinese characters in images. The proposed algorithm make the text content cover the background in a natural way. To validate the proposed method effective, another dataset are generated by ordinary fusion method. Two dataset are used to train Faster-RCNN network. And the experimental result shows that the dataset are generated by proposed method achieve a better performance of detection than the normal way.
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This work is supported by Anhui Provincial Natural Science Foundation (grant number 1608085MF136).
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Gao, Ww., Zhang, J., Chen, P., Wang, B., Xia, Y. (2018). Chinese Text Detection Using Deep Learning Model and Synthetic Data. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_46
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