• DocumentCode
    2396955
  • Title

    The application of directional wavelets in multiscale representation of pulp fibre image

  • Author

    Hou, Bei-Ping ; Wen Zhu

  • Author_Institution
    Inst. of Ind. Process Control, Zhejiang Univ., Hangzhou, China
  • Volume
    7
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    4314
  • Abstract
    This work proposes a novel algorithm to decompose fibre image and extract its edge characteristics. Because the characteristics of the paper fibre such as length and width play an important role in papermaking industry, so how to measure its related characteristics is important to improve the paper quality and production. An online fibre analyzer is designed based on the computer vision theory, and the distribution structure of the online fibres on image presents the multi-directional properties, so the multi-direction and multi-scale algorithm is proposed, and the directional wavelet transform is applied to the analysis of fibre image. Our analysis shows that directional wavelet transform can better reflect the edge information of images, because direction and texture information of fibre image can be better expressed. The experiment proves that the directional characterizations of fibre image can be extracted effectively.
  • Keywords
    computer vision; edge detection; fibres; image representation; image texture; paper industry; paper pulp; wavelet transforms; computer vision theory; directional wavelet transforms; edge characteristics extraction; fibre distribution structure; fibre image decomposition; image edge information; image extraction; image texture; multidirectional algorithm; multiscale algorithm; online fibre analyzer; paper production; paper quality; papermaking industry; pulp fibre image analysis; Algorithm design and analysis; Computer vision; Image analysis; Image texture analysis; Length measurement; Optical fiber theory; Production; Pulp and paper industry; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1384595
  • Filename
    1384595