Multi-resolution Texture Classification Based on Local Image Orientation

  • Ovidiu Ghita
  • Paul F. Whelan
  • Dana E. Ilea
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5112)


The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image orientation is extracted using the partial derivatives of the Gaussian function. Since the texture descriptors are dependent on the observation scale, in this study the main emphasis is placed on the implementation of multi-resolution texture analysis schemes. The experimental results were obtained when the analysed texture descriptors were applied to standard texture databases.


Local image orientation texture classification SVM multi-resolution 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ovidiu Ghita
    • 1
  • Paul F. Whelan
    • 1
  • Dana E. Ilea
    • 1
  1. 1.Vision Systems GroupDublin City UniversityDublin 9Ireland

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