Laser & Optoelectronics Progress, Volume. 57, Issue 21, 210101(2020)

Shape Object Matching Recognition of Turbulence Clutter Based on Improved Shape Context

Xu Xinggui1,2,3, Ran Bing1,3, Yang Ping1, Xian Hao1, and Liu Yong2
Author Affiliations
  • 1中国科学院光电技术研究所, 四川 成都 610209
  • 2电子科技大学光电科学与工程学院, 四川 成都 610054
  • 3中国科学院大学, 北京 100049
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    Figures & Tables(13)
    Schematic of OSC description operator construction
    Feature histogram extracted by OSC descriptor. (a) Marking point 1; (b) marking point 2; (c) marking point 3
    Schematic of imposing edge continuity constraint
    Flow chart of algorithm implementation
    Simulation shape point sets under turbulence clutter scene. (a) Original image; (b) shape simultaneously degraded by rotation and deformation; (c) turbulence clutter degraded by deformation, outliers, and rotation; (d) strong turbulence clutter shapes degraded by deformation, outliers, and rotation
    Long distance imaging data. (a)(b) Image data in turbulent clutter scene; (c)(d) manual model shape point set of personal car and truck
    Average matching error and the experimental parameters
    Matching results of proposed method for deformable target ‘Fish’ in turbulent clutter scene. (a) Target matching results in both turbulent noise and rotating scene; (b) target matching results in turbulent noise scene
    Matching results of different methods for non-grid deformable target ‘Fu’ in turbulent clutter scene. (a) APM method [5]; (b) IDSC method[8]; (c) proposed method
    Matching results of different methods for grid deformable target ‘personal car’ in actual outfield turbulence clutter scene. (a) Acquired image and enlarged target; (b) contour shape point set target obtained by method in Ref.[19]; (c) APM method [5]; (d) IDSC method[8]; (e) proposed method
    Matching results of different methods for grid deformable target ‘truck’ in actual outfield turbulence clutter scene. (a) Acquired image; (b) contour shape point set target obtained by method in Ref.[19]; (c) APM method [5]; (d) IDSC method[8]; (e) proposed method
    • Table 1. Average matching errors and processing time of different methods operating on three-type targets

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      Table 1. Average matching errors and processing time of different methods operating on three-type targets

      MethodAverage matching errorProcessing time /s
      FishFuF-16
      APM method[5]0.090.150.525.41
      IDSC method[8]0.110.170.641.39
      Proposed method0.030.120.140.87
    • Table 2. Average matching errors and processing time of different methods operating on the two-type outfield turbulence-cluttered sequences

      View table

      Table 2. Average matching errors and processing time of different methods operating on the two-type outfield turbulence-cluttered sequences

      MethodAverage matching errorProcessing time /s
      Personal carTruck
      APM method[5]0.100.357.62
      IDSC method[8]0.070.392.15
      Proposed method0.050.311.08
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    Xu Xinggui, Ran Bing, Yang Ping, Xian Hao, Liu Yong. Shape Object Matching Recognition of Turbulence Clutter Based on Improved Shape Context[J]. Laser & Optoelectronics Progress, 2020, 57(21): 210101

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Dec. 23, 2019

    Accepted: --

    Published Online: Oct. 24, 2020

    The Author Email:

    DOI:10.3788/LOP57.210101

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