• DocumentCode
    2110924
  • Title

    Fabric Defect Detection Based on Wavelet Decomposition with One Resolution Level

  • Author

    Guan, Shengqi ; Shi, Xiuhua

  • Author_Institution
    Coll. of Marine Eng., Northwestern Polytech. Univ., Xian
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    281
  • Lastpage
    285
  • Abstract
    According to the property of wavelet transform and fabric texture´s Fourier spectrum, a new method for defect detection was presented. The proposed method is based on wavelet lifting transform with one resolution level. By using restoration scheme of the Fourier transform, the normal fabric textures of smooth sub-image in the spatial domain are removed by detecting the high-energy frequency components of sub-image in the Fourier domain, setting them to zero using frequency-domain filter, and back-transforming to a spatial domain sub-image. Then, the smooth and detail sub-images are segmented into many sub-windows, in which standard deviation are calculated as extracted features. The extracted features are compared with normal sub-window´s features to determine whether there exists defect. Experimental results show that this method is validity and feasibility.
  • Keywords
    Fourier transforms; fabrics; feature extraction; image resolution; image restoration; image segmentation; production engineering computing; wavelet transforms; Fourier transform; fabric defect detection; fabric texture; feature extraction; frequency-domain filter; high-energy frequency component; image segmentation; resolution level; restoration scheme; wavelet decomposition; wavelet lifting transform; Defect detection; fourier transform; frequency-domain filter; lifting scheme; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering, 2008. ISISE '08. International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-2727-4
  • Type

    conf

  • DOI
    10.1109/ISISE.2008.139
  • Filename
    4732218