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Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1815007(2022)

Improved Manifold Ranking Algorithm for Green Citrus Recognition

Chunjian Hua1,2、*, Zijun Zhang1,2, Yi Jiang1,2, Jianfeng Yu1,2, and Ying Chen3
Author Affiliations
  • 1School of Mechanical Engineering, Jiangnan University, Wuxi 214122, Jiangsu , China
  • 2Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology, Wuxi 214122, Jiangsu , China
  • 3School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, Jiangsu , China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (15)
    References (20)
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    Figures & Tables(10)
    Flow chart of the proposed algorithm

    Fig. 1. Flow chart of the proposed algorithm

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    Image brightness enhancement result. (a) Original image; (b) image after brightness enhancement

    Fig. 2. Image brightness enhancement result. (a) Original image; (b) image after brightness enhancement

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    Superpixel segmentation result. (a) Brightness enhancement image; (b) super pixel segmentation image

    Fig. 3. Superpixel segmentation result. (a) Brightness enhancement image; (b) super pixel segmentation image

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    Convex hull results of Harris corner detection

    Fig. 4. Convex hull results of Harris corner detection

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    RTV structure extraction and LC feature images. (a) Brightness enhancement; (b) RTV de-texturing; (c) LC feature image; (d) after screening

    Fig. 5. RTV structure extraction and LC feature images. (a) Brightness enhancement; (b) RTV de-texturing; (c) LC feature image; (d) after screening

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    Preliminary foreground extraction result. (a) Canny edge detection; (b) feature fusion; (c) preliminary foreground result

    Fig. 6. Preliminary foreground extraction result. (a) Canny edge detection; (b) feature fusion; (c) preliminary foreground result

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    Improved background prior method. (a) After brightness enhancement; (b) GMR method; (c) proposed method

    Fig. 7. Improved background prior method. (a) After brightness enhancement; (b) GMR method; (c) proposed method

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    Result comparison of different algorithms. (a) After brightness enhancement; (b) ITTi; (c) SR; (d) FT; (e) CA; (f) GMR; (g) proposed algorithm

    Fig. 8. Result comparison of different algorithms. (a) After brightness enhancement; (b) ITTi; (c) SR; (d) FT; (e) CA; (f) GMR; (g) proposed algorithm

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    Comparison of segmentation results. (a) GMR; (b) proposed algorithm; (c) artificial segmentation

    Fig. 9. Comparison of segmentation results. (a) GMR; (b) proposed algorithm; (c) artificial segmentation

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    • Table 1. Evaluation of segmentation results

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      Table 1. Evaluation of segmentation results

      Image numberGMR algorithmProposed algorithm
      SA /%FPR /%FNR /%SA /%FPR /%FNR /%
      Average65.1721.843.1494.223.191.64
      167.8319.880.3892.334.361.56
      271.665.868.2797.120.800.37
      354.7527.452.6395.962.051.41
      471.7123.970.1795.873.740.76
      580.0312.490.2296.561.181.35
      674.6521.910.0397.751.520.98
      754.1029.111.3291.366.970.31
      881.948.511.6592.183.131.49
      942.8025.5013.4490.053.363.11
      1050.4528.505.8997.390.681.52
      1169.9314.535.0792.542.782.32
      1293.433.600.7090.512.314.59
      1358.7833.982.3795.124.990.93
      1440.2750.471.8194.406.822.21
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    Chunjian Hua, Zijun Zhang, Yi Jiang, Jianfeng Yu, Ying Chen. Improved Manifold Ranking Algorithm for Green Citrus Recognition[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1815007

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    Paper Information

    Category: Machine Vision

    Received: Jun. 28, 2021

    Accepted: Jul. 28, 2021

    Published Online: Aug. 29, 2022

    The Author Email: Hua Chunjian (cjhua@jiangnan.edu.cn)

    DOI:10.3788/LOP202259.1815007

    Topics

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