Laser & Optoelectronics Progress, Volume. 58, Issue 24, 2410001(2021)

Microscopic Image Mosaic Algorithm Using Improved Optical Flow Method

Qing Chen, Haiyang Zhou, and Feihong Yu*
Author Affiliations
  • College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
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    Figures & Tables(13)
    Flow chart of proposed method
    Image overlap area
    Original images
    Stitching results. (a) Autostitch method; (b) template matching method; (c) optical flow method; (d) proposed method
    Original images
    Point matching results before and after improvement
    Stitching results before and after improvement. (a)(c) Before improvement; (b)(d) after improvement
    Correct matching rate before and after adding constraints
    Original images for mosaic test
    Results of mosaic test
    Panorama of microscopic slices. (a) Overall stitching performance of proposed method; (b)-(d) stitching detail
    • Table 1. Running time of different algorithms

      View table

      Table 1. Running time of different algorithms

      AlgorithmAutostitchTemplate matchingOptical flowProposed method
      Time /s3.7800.2780.2160.121
    • Table 2. Analysis of accuracy rate before and after adding constraints

      View table

      Table 2. Analysis of accuracy rate before and after adding constraints

      GroupNumber of matchesNumber of matches after eliminate outlierNumber of correct matchesAccuracy /%
      113213012293.85
      13212311696.75
      21311205344.17
      131151173.33
      31211087266.67
      121544583.33
      412312010486.67
      123908695.56
      5108986162.24
      108332781.31
      6105978981.82
      105878496.55
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    Qing Chen, Haiyang Zhou, Feihong Yu. Microscopic Image Mosaic Algorithm Using Improved Optical Flow Method[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2410001

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    Paper Information

    Category: Image Processing

    Received: Dec. 11, 2020

    Accepted: Feb. 12, 2021

    Published Online: Nov. 24, 2021

    The Author Email: Feihong Yu (feihong@zju.edu.cn)

    DOI:10.3788/LOP202158.2410001

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