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Infrared and Laser Engineering, Volume. 50, Issue S2, 20211057(2021)

Automatic recognition algorithm of digital instrument reading in offshore booster station based on Mask-RCNN

Peng Tang1,2, Yi Liu3, Hongguang Wei2, Xiufen Dong1, Guobin Yan4, Yingbin Zhang4, Yajun Yuan4, Zengguang Wang3, Yanan Fan3, and Pengge Ma2
Author Affiliations
  • 1China Three Gorges Corporation, Beijing 100038, China
  • 2School of Intelligent Engineering, Zhengzhou Institute of Aeronautics Industry Management, Zhengzhou 450015, China
  • 3Luoyang Institute of Electro-Optical Equipment, Aviation Industry Corporation of China, Luoyang 471000, China
  • 4Three Gorges New Energy Offshore Wind Power Operation and Maintenance Jiangsu Co., Ltd, Yancheng 224008, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (12)
    References (17)
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    Figures & Tables(10)
    Images before and after brightness equalization with GrayWorld algorithm

    Fig. 1. Images before and after brightness equalization with GrayWorld algorithm

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    Corrected tilted-image experiment effect

    Fig. 2. Corrected tilted-image experiment effect

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    YOLOv3 digital identification process

    Fig. 3. YOLOv3 digital identification process

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    Mask-RCNN structure

    Fig. 4. Mask-RCNN structure

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    Return to the window

    Fig. 5. Return to the window

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    Feature map graphic

    Fig. 6. Feature map graphic

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    Partial data set

    Fig. 7. Partial data set

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    Loss function curve

    Fig. 8. Loss function curve

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    Experimental result diagram

    Fig. 9. Experimental result diagram

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    • Table 1. Comparison of different recognition methods on data sets

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      Table 1. Comparison of different recognition methods on data sets

      ModelTest set /frame AccuracyTime consuming/ms
      YOLOv310099.03%20.2
      Mask-RCNN10099.52%212
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    Peng Tang, Yi Liu, Hongguang Wei, Xiufen Dong, Guobin Yan, Yingbin Zhang, Yajun Yuan, Zengguang Wang, Yanan Fan, Pengge Ma. Automatic recognition algorithm of digital instrument reading in offshore booster station based on Mask-RCNN[J]. Infrared and Laser Engineering, 2021, 50(S2): 20211057

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    Paper Information

    Category: Image processing

    Received: May. 10, 2021

    Accepted: --

    Published Online: Dec. 3, 2021

    The Author Email:

    DOI:10.3788/IRLA20211057

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology