• Infrared and Laser Engineering
  • Vol. 50, Issue S2, 20211057 (2021)
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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    DOI: 10.3788/IRLA20211057 Cite this Article
    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 Copy Citation Text show less
    Images before and after brightness equalization with GrayWorld algorithm
    Fig. 1. Images before and after brightness equalization with GrayWorld algorithm
    Corrected tilted-image experiment effect
    Fig. 2. Corrected tilted-image experiment effect
    YOLOv3 digital identification process
    Fig. 3. YOLOv3 digital identification process
    Mask-RCNN structure
    Fig. 4. Mask-RCNN structure
    Return to the window
    Fig. 5. Return to the window
    Feature map graphic
    Fig. 6. Feature map graphic
    Partial data set
    Fig. 7. Partial data set
    Loss function curve
    Fig. 8. Loss function curve
    Experimental result diagram
    Fig. 9. Experimental result diagram
    ModelTest set /frame AccuracyTime consuming/ms
    YOLOv310099.03%20.2
    Mask-RCNN10099.52%212
    Table 1. Comparison of different recognition methods on data sets
    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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