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Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0210014(2021)

Image Segmentation Algorithm of Mesh Fabric Based on Regional Minimum Gray Value

Chunjian Hua1,2、*, Kangkang Sun1,2, and Ying Chen3
Author Affiliations
  • 1School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
  • 2Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology, Wuxi, Jiangsu 214122, China;
  • 3School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
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    AbstractGet PDF(in Chinese)
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    Comparison results before and after preprocessing. (a) Image pyramid; (b) original image; (c) image after preprocessing

    Fig. 1. Comparison results before and after preprocessing. (a) Image pyramid; (b) original image; (c) image after preprocessing

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    Grayscale variation image of local section of mesh. (a) Local image of mesh fabric; (b) distribution curve of gray value in local linear neighborhood

    Fig. 2. Grayscale variation image of local section of mesh. (a) Local image of mesh fabric; (b) distribution curve of gray value in local linear neighborhood

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    Mesh fabric images with three different light levels. (a) Sample 1; (b) sample 2; (c) sample 3

    Fig. 3. Mesh fabric images with three different light levels. (a) Sample 1; (b) sample 2; (c) sample 3

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    Results of segmenting sample 1 with different thresholds and its partial enlarged views. (a) T=20; (b) T=50; (c) T=100; (d) proposed algorithm; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

    Fig. 4. Results of segmenting sample 1 with different thresholds and its partial enlarged views. (a) T=20; (b) T=50; (c) T=100; (d) proposed algorithm; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

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    Results of segmenting sample 2 with different thresholds and its partial enlarged views. (a) T=20; (b) T=50; (c) T=100; (d) proposed algorithm; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

    Fig. 5. Results of segmenting sample 2 with different thresholds and its partial enlarged views. (a) T=20; (b) T=50; (c) T=100; (d) proposed algorithm; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

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    Results of segmenting sample 3 with different thresholds and its partial enlarged views. (a) T=20; (b) T=50; (c) T=100; (d) proposed algorithm; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

    Fig. 6. Results of segmenting sample 3 with different thresholds and its partial enlarged views. (a) T=20; (b) T=50; (c) T=100; (d) proposed algorithm; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

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    Results of segmenting sample 1 with different algorithms and its partial enlarged views. (a) Shading threshold algorithm; (b) marking watershed algorithm; proposed algorithm (c) before preprocessing, (d) after preprocessing; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

    Fig. 7. Results of segmenting sample 1 with different algorithms and its partial enlarged views. (a) Shading threshold algorithm; (b) marking watershed algorithm; proposed algorithm (c) before preprocessing, (d) after preprocessing; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

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    Results of segmenting sample 2 with different algorithms and its partial enlarged segmenting. (a) Shading threshold algorithm; (b) marking watershed algorithm; proposed algorithm (c) before preprocessing, (d) after preprocessing; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

    Fig. 8. Results of segmenting sample 2 with different algorithms and its partial enlarged segmenting. (a) Shading threshold algorithm; (b) marking watershed algorithm; proposed algorithm (c) before preprocessing, (d) after preprocessing; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

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    Results of segmenting sample 3 with different algorithms and its partial enlarged views. (a) Shading threshold algorithm; (b) marking watershed algorithm; proposed algorithm (c) before preprocessing, (d) after preprocessing; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

    Fig. 9. Results of segmenting sample 3 with different algorithms and its partial enlarged views. (a) Shading threshold algorithm; (b) marking watershed algorithm; proposed algorithm (c) before preprocessing, (d) after preprocessing; (e) partial enlargement of Fig. (a); (f) partial enlargement of Fig. (b); (g) partial enlargement of Fig. (c); (h) partial enlargement of Fig. (d)

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    • Table 1. Number of mesh segmentation errors and segmentation error rate

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      Table 1. Number of mesh segmentation errors and segmentation error rate

      AlgorithmSample 1Sample 2Sample 3
      Number ofsegmentationerrorsSegmentationerrorrate/%Number ofsegmentationerrorsSegmentationerrorrate/%Number ofsegmentationerrorsSegmentationerrorrate/%
      Mark watershedalgorithm4111.0214.8103.3
      ProposedalgorithmsBeforepreprocessing16243.018341.17424.3
      Afterpreprocessing10.310.200

    • Table 2. Comparison of mesh segmentation results of different algorithms

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      Table 2. Comparison of mesh segmentation results of different algorithms

      AlgorithmMark watershedalgorithmProposed algorithm
      Before preprocessingAfter preprocessing
      Number of meshes34932
      Number of mesh segmentation errors20611174184
      Segmentation error rate/%5.9033.610.24
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    Chunjian Hua, Kangkang Sun, Ying Chen. Image Segmentation Algorithm of Mesh Fabric Based on Regional Minimum Gray Value[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0210014

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    Paper Information

    Category: Image Processing

    Received: Jun. 4, 2020

    Accepted: Jul. 16, 2020

    Published Online: Jan. 8, 2021

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

    DOI:10.3788/LOP202158.0210014

    Topics

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