Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410008(2021)

Fabric Defect Detection Method Based on Coarseness Measurement and Color Distance

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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    References(19)

    [1] Zhang H H, Ma J X, Jing J F et al. Fabric defect detection method based on improved fast weighted Median filtering and K-means[J]. Journal of Textile Research, 40, 50-56(2019).

    [7] Alper Selver M, Avşar V, Özdemir H. Textural fabric defect detection using statistical texture transformations and gradient search[J]. The Journal of the Textile Institute, 105, 998-1007(2014).

    [9] [9] Hou XD, Zhang LQ. Saliency detection: a spectral residual approach[C]∥2007 IEEE Conference on Computer Vision and Pattern Recognition, June 17-22, 2007, Minneapolis, MN, USA. New York: IEEE Press, 2007: 1- 8.

    [11] Zhu S W, Hao C Y. Fabric defect detection approach based on texture periodicity analysis[J]. Computer Engineering and Applications, 48, 163-166(2012).

    [16] Song Y M, Yuan D L. Research of defect detection of cord fabrics based on Fourier transform[J]. Chinese Journal of Scientific Instrument, 27, 1695-1697(2006).

    [17] Tamura H, Mori S J, Yamawaki T. Textural features corresponding to visual perception[J]. IEEE Transactions on Systems, Man, and Cybernetics, 8, 460-473(1978).

    [18] Achanta R, Hemami S, Estrada F et al. Frequency-tuned salient region detection[C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL, USA., 1597-1604(2009).

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    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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    Paper Information

    Category: Image Processing

    Received: Jun. 16, 2020

    Accepted: Aug. 6, 2020

    Published Online: Feb. 8, 2021

    The Author Email: Zhu Lei (zhulei791014@163.com)

    DOI:10.3788/LOP202158.0410008

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