Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Tobacco Retail License Recognition Based on Dual Attention Mechanism

  • Shan, Yuxiang (Chinese Tobacco Zhejiang Industrial Company Limited) ;
  • Ren, Qin (Chinese Tobacco Zhejiang Industrial Company Limited) ;
  • Wang, Cheng (Chinese Tobacco Zhejiang Industrial Company Limited) ;
  • Wang, Xiuhui (Dept. of Computer, China Jiliang University)
  • Received : 2022.01.27
  • Accepted : 2022.06.15
  • Published : 2022.08.31
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Abstract

Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.

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Acknowledgement

This work in this paper was supported by the Research on Key Technology and Application of Marketing Robot Process Automation (RPA) Based on Intelligent Image Recognition in Zhejiang China Tobacco Industry Co. Ltd. (No. ZJZY2021E001).

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