Scene Text Detection Based on Feature Fusion Network
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    Abstract:

    At present, scene text detection based on deep learning has achieved good performance in complex background. However, it is difficult to precisely detect text with small scale. To solve this problem, this study proposes a deep neural network based on feature fusion, and a new neural network with senior semantic is constructed by combining the high-level feature and low-level feature of traditional deep neural network. Strong semantic information of the high layer network is utilized to improve the overall performance of the neural network, and the feature fusion network directly predicts text with multiple scales through multiple output layers. Experimental results on ICDAR2011 and ICDAR2013 datasets show that proposed method is significantly effective in detecting small scale text. Meanwhile, the proposed method has high accuracy and robustness in scene text detection, and the F-measure achieves 0.83 on both datasets.

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余峥,王晴晴,吕岳.基于特征融合网络的自然场景文本检测.计算机系统应用,2018,27(10):1-10

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  • Received:February 02,2018
  • Revised:February 28,2018
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  • Online: September 29,2018
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