• DocumentCode
    1742376
  • Title

    Graph-based features for texture discrimination

  • Author

    Grigorescu, C. ; Petkov, Nicolai

  • Author_Institution
    Dept. of Comput. Sci., Groningen Univ.
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1076
  • Abstract
    Graph-based features, such as the number of connected components, edges of a given orientation and vertices per unit area, and the number of vertices and pixels per connected component, are proposed for the analysis of textures which consist of structural elements. The proposed set of features is compared with features obtained by a typical filter-based scheme which makes use of Gabor filters. The discrimination properties of the two types of features are assessed by evaluating the separability of sets of feature vectors which are derived from different types of texture using the Mahalanobis distance. The graph-based features are shown to be superior to the filter-based features for the class of concerned textures. They are particularly suited for discrimination between textures which have the same spatial and orientation regularity but consist of elements of different forms
  • Keywords
    feature extraction; filtering theory; graph theory; image representation; image texture; Gabor filters; Mahalanobis distance; feature extraction; graph representation; graph-based features; image texture; texture discrimination; Feature extraction; Gabor filters; Maximum likelihood detection; Nonlinear filters; Pixel; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.903732
  • Filename
    903732