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Laser & Optoelectronics Progress, Volume. 58, Issue 20, 2010001(2021)

Improved Laser Point Cloud Filtering Algorithm

Haoyu Han**, Yuan Zhang*, and Xie Han
Author Affiliations
  • College of Big Data, North University of China, Taiyuan, Shanxi 030051, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
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    References (16)
    Cited By (3)
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    Figures & Tables(11)
    Results of statistical filtering algorithm before and after processing. (a) Initial scanning point cloud; (b) point cloud after processing

    Fig. 1. Results of statistical filtering algorithm before and after processing. (a) Initial scanning point cloud; (b) point cloud after processing

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    Results of different tensor voting methods. (a) Normal tensor voting method; (b) point tensor voting method

    Fig. 2. Results of different tensor voting methods. (a) Normal tensor voting method; (b) point tensor voting method

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    Estimated results at different K values. (a) K=15; (b) K=5

    Fig. 3. Estimated results at different K values. (a) K=15; (b) K=5

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    Filtering results of noise plane

    Fig. 4. Filtering results of noise plane

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    Point clouds of bird bottle model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

    Fig. 5. Point clouds of bird bottle model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

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    Point clouds of hand model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

    Fig. 6. Point clouds of hand model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

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    Point clouds of buddha model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

    Fig. 7. Point clouds of buddha model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

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    Point clouds of stone model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

    Fig. 8. Point clouds of stone model under different algorithms. (a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

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    Point clouds of tortoise model under different algorithms.(a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

    Fig. 9. Point clouds of tortoise model under different algorithms.(a) Initial point cloud; (b) proposed algorithm; (c) Ref. [4]; (d) Ref. [5]

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    • Table 1. Ratio of number of points between filter model and noiseless model unit: %

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      Table 1. Ratio of number of points between filter model and noiseless model unit: %

      ModelProposed algorithmRef. [4]Ref. [5]
      Bird bottle97.9085.0985.59
      Hand99.7697.5898.07
      Buddha98.9992.8096.01
      Stone99.8793.7295.87
      Tortoise99.2389.9093.31

    • Table 2. Points and processing time of different models

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      Table 2. Points and processing time of different models

      ModelPointsRunning time of proposed algorithm/sRunning time of Ref. [4] /sRunning time of Ref. [5] /s
      Bird bottle3777831.316.629.3
      Hand5075638.818.329.6
      Buddha2932526.715.423.8
      Stone1540620.313.218.9
      Tortoise2293922.414.721.2
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    Haoyu Han, Yuan Zhang, Xie Han. Improved Laser Point Cloud Filtering Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010001

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    Paper Information

    Category: Image Processing

    Received: Nov. 25, 2020

    Accepted: Dec. 27, 2020

    Published Online: Oct. 12, 2021

    The Author Email: Han Haoyu (985811696@qq.com), Zhang Yuan (68229275@qq.com)

    DOI:10.3788/LOP202158.2010001

    Topics

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