• DocumentCode
    677323
  • Title

    The fabric defect detection technology based on wavelet transform and neural network convergence

  • Author

    Zhiqiang Kang ; Chaohui Yuan ; Qian Yang

  • Author_Institution
    Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2013
  • fDate
    26-28 Aug. 2013
  • Firstpage
    597
  • Lastpage
    601
  • Abstract
    Methods to fabric defects detection are varied, but the common method to detect the fabric defect shapes is slow and poor accuracy. Based on wavelet transform and neural network convergence technologies, this paper presents a new detection method on the fabric defect, which takes full advantage of wavelet transform good time-frequency localization characteristics and multi-scale image analysis capabilities on the fabric defect extraction, neural network technology can against defects for precise identification of the fabric for rapid detection.
  • Keywords
    automatic optical inspection; fabrics; flaw detection; neural nets; production engineering computing; time-frequency analysis; wavelet transforms; detection method; fabric defect detection technology; fabric defect extraction; multiscale image analysis capability; neural network convergence; neural network technology; rapid detection; time-frequency localization characteristics; wavelet transform; Fabrics; Frequency-domain analysis; Gabor filters; Multiresolution analysis; Neural networks; Wavelet transforms; Defect Detection; Neural Network; Rapid detection; Wavelet Transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2013 IEEE International Conference on
  • Conference_Location
    Yinchuan
  • Type

    conf

  • DOI
    10.1109/ICInfA.2013.6720367
  • Filename
    6720367