• DocumentCode
    382140
  • Title

    Eigenvector method for texture recognition

  • Author

    Carcassoni, Marco ; Ribeiro, Eraldo ; Hancock, Edwin R.

  • Author_Institution
    Dept. of Comput. Sci., York Univ., UK
  • Volume
    3
  • fYear
    2002
  • fDate
    2002
  • Abstract
    In this paper we investigate how texture recognition can be achieved through the modal analysis of the pattern of peaks in the spectral density function. We commence from a texture characterisation which is based on the positions of peaks in the power spectrum. Our aim is to use the modal structure of the pattern of peaks to perform texture retrieval from an image data-base. We explore two different approaches to the problem. First, we use a variant of the Shapiro and Brady method to perform recognition by comparing the modal structure of the proximity matrix for peak cluster centres. Second, we perform latent semantic indexing on vectors representing the polar distribution of frequency peaks. We provide and experimental evaluation of these two methods on a data-base of fabric and wrapping paper patterns.
  • Keywords
    eigenvalues and eigenfunctions; image recognition; image texture; spectral analysis; visual databases; Shapiro and Brady method; eigenvector method; fabric patterns; frequency peaks; image data-base; latent semantic indexing; modal structure; peak cluster centres; polar distribution; power spectrum; proximity matrix; spectral density function; texture characterisation; texture recognition; wrapping paper patterns; Autocorrelation; Computer science; Density functional theory; Frequency domain analysis; Frequency estimation; Image retrieval; Indexing; Information retrieval; Modal analysis; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing. 2002. Proceedings. 2002 International Conference on
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-7622-6
  • Type

    conf

  • DOI
    10.1109/ICIP.2002.1038970
  • Filename
    1038970