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Laser & Optoelectronics Progress, Volume. 56, Issue 21, 211006(2019)

Damage Detection of Metal Parts by Combining Information Entropy and Low-Rank Tensor Analysis

Peng Yang1, Deer Liu1、*, Ruixue Li1, Jingyu Liu1, and Heyuan Zhang2
Author Affiliations
  • 1School of Architectural and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China;
  • 2College of Chinese & Asean Arts, Chengdu University, Chengdu, Sichuan 610106, China;
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    AbstractGet PDF(in Chinese)
    Figures&Tables (7)
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    References (19)
    Cited By (2)
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    Figures & Tables(7)
    Data acquisition platform

    Fig. 1. Data acquisition platform

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    Matrix amplification

    Fig. 2. Matrix amplification

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    Metal parts

    Fig. 3. Metal parts

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    Edge extraction. (a) Sobel algorithm; (b) Roberts algorithm; (c) Prewitt; (d) Log; (e) Canny; (f) G&C; (g) algorithm in Ref. [4]; (h) algorithm in Ref. [17]; (i) algorithm in Ref. [16]; (j) algorithm in Ref. [14]; (k) difference entropy matrix Tc of the proposed algorithm; (l) weighted difference entropy matrix Tc' of the proposed algorithm

    Fig. 4. Edge extraction. (a) Sobel algorithm; (b) Roberts algorithm; (c) Prewitt; (d) Log; (e) Canny; (f) G&C; (g) algorithm in Ref. [4]; (h) algorithm in Ref. [17]; (i) algorithm in Ref. [16]; (j) algorithm in Ref. [14]; (k) difference entropy matrix Tc of the proposed algorithm; (l) weighted difference entropy matrix Tc' of the proposed algorithm

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    Tensor analysis. (a) Sobel; (b) Roberts; (c) Prewitt; (d) Log; (e) Canny; (f) G&C; (g) algorithm in Ref. [4]; (h) algorithm in Ref. [17]; (i) algorithm in Ref. [16]; (j) algorithm in Ref. [14]; (k) Tc-tensor of the proposed algorithm; (l) Tc'-tensor of the proposed algorithm

    Fig. 5. Tensor analysis. (a) Sobel; (b) Roberts; (c) Prewitt; (d) Log; (e) Canny; (f) G&C; (g) algorithm in Ref. [4]; (h) algorithm in Ref. [17]; (i) algorithm in Ref. [16]; (j) algorithm in Ref. [14]; (k) Tc-tensor of the proposed algorithm; (l) Tc'-tensor of the proposed algorithm

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    • Table 1. Accuracy test

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      Table 1. Accuracy test

      MethodRR'CY /%CQ
      Sobel1166371131.40.116
      Roberts1540531229.00.154
      Prewitt1187358833.10.118
      Log1357530525.60.135
      Canny19691974210.00.196
      G&C19691974210.00.196
      D-S3258404880.50.325
      D-QS79387690.50.079
      Ref. [4]3449468073.70.344
      Ref. [17]671196234.20.067
      Ref. [16]593159937.10.059
      Ref. [14]2918655444.50.291

    • Table 2. Robustness test

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      Table 2. Robustness test

      NoiseRR'CY /%CQ
      0.0223466443178.20.346
      0.0323325443075.10.332
      0.0393217437073.60.321
      0.0453348561559.60.334
      0.0502166286175.70.216
      0.0553180766241.50.317
      0.0592089347960.00.208
      0.0632827827134.20.282
      0.06728011199623.30.280
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    Peng Yang, Deer Liu, Ruixue Li, Jingyu Liu, Heyuan Zhang. Damage Detection of Metal Parts by Combining Information Entropy and Low-Rank Tensor Analysis[J]. Laser & Optoelectronics Progress, 2019, 56(21): 211006

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    Paper Information

    Category: Image Processing

    Received: Mar. 29, 2019

    Accepted: May. 5, 2019

    Published Online: Nov. 2, 2019

    The Author Email: Deer Liu (landserver@163.com)

    DOI:10.3788/LOP56.211006

    Topics

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