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International Conference on Artificial Intelligence and Security

ICAIS 2020: Artificial Intelligence and Security pp 545–556Cite as

Machine Vision Based Novel Scheme for Largely, Reducing Printing Errors in Medical Package

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12240))

Abstract

Aiming at the problem of misprint or obscure of production date, batch number and the validity on the medicine package, a delay-based misplaced difference scheme for medical information detection is put forward. To be specific, medical images with delay in packaging are acquired by a vision detection system, based on which, character images are obtained through misplaced subtraction operation; and a convolution kernel is designed based on gray value distribution of the character images for multi-step convolution to remove speckle noise. Then a specific operation with corrosion and dilation is further utilized to remove speckle noise and enhance the target character area. In the end, the modified weighted median filter is adopted for noise inhibition to further improve the recognition accuracy. Experimental results show that when the double image overlap η is 80% and threshold λ (the percentage of non-zero gray values in each convolution block) is 60%, the scheme’s recognition can be as accurate as 97.8% and detection speed can reach up to 0.1373 s/image, the detection precision and efficiency can satisfy medical information recognition requirements in medical package.

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Author information

Authors and Affiliations

  1. School of Cyber Security, Qilu University of Technology, Shandong, 250353, China

    Bin Ma, Qi Li, Xiaoyu Wang & Chunpeng Wang

  2. School of Information Science and Technology, Dalian Martime University, Dalian, 116026, China

    Qi Li & Xiaoyu Wang

  3. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, 07102, USA

    Yunqing Shi

Authors
  1. Bin Ma
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  2. Qi Li
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  3. Xiaoyu Wang
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  4. Chunpeng Wang
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  5. Yunqing Shi
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Corresponding authors

Correspondence to Bin Ma , Qi Li or Xiaoyu Wang .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science, Nanjing, China

    Jinwei Wang

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Ma, B., Li, Q., Wang, X., Wang, C., Shi, Y. (2020). Machine Vision Based Novel Scheme for Largely, Reducing Printing Errors in Medical Package. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Lecture Notes in Computer Science(), vol 12240. Springer, Cham. https://doi.org/10.1007/978-3-030-57881-7_48

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  • DOI: https://doi.org/10.1007/978-3-030-57881-7_48

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57880-0

  • Online ISBN: 978-3-030-57881-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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