• DocumentCode
    2030432
  • Title

    Structural Texture Segmentation using Affine Symmetry

  • Author

    Park, Heechan ; Martin, Graham R. ; Bhalerao, Abhir H.

  • Author_Institution
    Univ. of Warwick, Coventry
  • Volume
    2
  • fYear
    2007
  • fDate
    Sept. 16 2007-Oct. 19 2007
  • Abstract
    Many natural textures comprise structural patterns and show strong self-similarity. We use affine symmetry to segment an image into self-similar regions; that is a patch of texture (blocks from a uniformly partitioned image) can be transformed to other similar patches by warping. If the texture image contains multiple regions, we then cluster patches into a number of classes such that the overall warping error is minimized. Discovering the optimal clusters is not trivial and known methods are computationally intensive due to the affine transformation. We demonstrate efficient segmentation of structural textures without affine computation. The algorithm uses Fourier Slice Analysis to obtain a spectral contour signature. Experimental evaluation on structural textures shows encouraging results and application on natural images demonstrates identification of texture objects.
  • Keywords
    Fourier analysis; affine transforms; image segmentation; image texture; natural scenes; object recognition; Fourier slice analysis; affine symmetry; affine transformation; image segmentation; image warping; natural images; object identification; optimal clusters; self-similar regions; spectral contour signature; structural patterns; structural texture segmentation; uniformly partitioned image; warping error; Algorithm design and analysis; Clustering algorithms; Computer science; Data mining; Feature extraction; Fourier transforms; Image processing; Image segmentation; Independent component analysis; Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2007. ICIP 2007. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1437-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2007.4379089
  • Filename
    4379089