• Laser & Optoelectronics Progress
  • Vol. 58, Issue 4, 0410008 (2021)
Mengfan Ren, Lei Zhu*, Xiaomin Ma, and Lin Cui
Author Affiliations
  • School of Electronics and Information, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
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    DOI: 10.3788/LOP202158.0410008 Cite this Article Set citation alerts
    Mengfan Ren, Lei Zhu, Xiaomin Ma, Lin Cui. Fabric Defect Detection Method Based on Coarseness Measurement and Color Distance[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410008 Copy Citation Text show less
    Flow chart of fabric defect detection method based on coarseness measurement and color distance
    Fig. 1. Flow chart of fabric defect detection method based on coarseness measurement and color distance
    Results of coarseness measurement and classification. (a) Simple texture fabric images; (b) complex texture fabric images
    Fig. 2. Results of coarseness measurement and classification. (a) Simple texture fabric images; (b) complex texture fabric images
    Defect rough location results of fabric images in Fig.2 using the proposed method. (a) Defect rough location results of simple texture fabric images; (b) defect rough location results of complex texture fabric images
    Fig. 3. Defect rough location results of fabric images in Fig.2 using the proposed method. (a) Defect rough location results of simple texture fabric images; (b) defect rough location results of complex texture fabric images
    Defect detection results of images in Fig.3 using the proposed method. (a) Defect detection results of simple texture fabric images; (b) defect detection results of complex texture fabric images
    Fig. 4. Defect detection results of images in Fig.3 using the proposed method. (a) Defect detection results of simple texture fabric images; (b) defect detection results of complex texture fabric images
    Comparison of defect detection results for periodic texture fabric images using different methods. (a) Periodic texture fabric images; (b) detection results by method in Ref. [1]; (c) detection results by method in Ref. [9]; (d) detection results by method in Ref. [12]; (e) detection results by method in Ref. [19]; (f) detection results of the proposed method
    Fig. 5. Comparison of defect detection results for periodic texture fabric images using different methods. (a) Periodic texture fabric images; (b) detection results by method in Ref. [1]; (c) detection results by method in Ref. [9]; (d) detection results by method in Ref. [12]; (e) detection results by method in Ref. [19]; (f) detection results of the proposed method
    MethodTPR /%FPR /%ACC /%tAV /s
    Method in Ref. [1]89.0018.0086.670.47
    Method in Ref. [9]81.0044.0072.670.15
    Method in Ref. [12]83.0026.0080.003.53
    Method in Ref. [19]86.0022.0083.3323.78
    Proposed method93.006.0093.332.38
    Table 1. Comparison of detection performance using different methods
    Mengfan Ren, Lei Zhu, Xiaomin Ma, Lin Cui. Fabric Defect Detection Method Based on Coarseness Measurement and Color Distance[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410008
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