• DocumentCode
    1705359
  • Title

    Texture inspection with self-adaptive convolution filters

  • Author

    Dewaele, P. ; Van Gool, L. ; Wambacq, A. ; Oosterlinck, A.

  • Author_Institution
    Catholic Univ. of Leuven, Belgium
  • fYear
    1988
  • Firstpage
    56
  • Abstract
    A resolution-independent method for detection of imperfections in quasi-periodic textures is described. After image standardization, the period is estimated in the horizontal and vertical directions. This determines the size of a sparse convolution mask. Mask coefficients are determined by the well-known technique of eigenfilter extraction. The method thus offers a completely automated generation of a bank of suitable filters, the form and the coefficients of which are made dependent on the texture type to be inspected. After feature extraction in the filtered images, a Mahalanobis classifier is applied
  • Keywords
    adaptive filters; eigenvalues and eigenfunctions; filtering and prediction theory; pattern recognition; picture processing; Mahalanobis classifier; eigenfilter extraction; feature extraction; flaw detection; image standardization; mask coefficients; pattern detection; picture processing; quasi-periodic textures; resolution-independent method; self-adaptive convolution filters; sparse convolution mask; texture inspection; Convolution; Fabrics; Feature extraction; Filter bank; Frequency domain analysis; Image edge detection; Inspection; Pattern analysis; Pixel; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1988., 9th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    0-8186-0878-1
  • Type

    conf

  • DOI
    10.1109/ICPR.1988.28171
  • Filename
    28171