@InProceedings{matas-scia09,
  IS = { zkontrolovano 29 Jan 2010 },
  UPDATE  = { 2009-09-23 },
  booktitle = { SCIA 2009: Proceedings of the 16th Scandinavian
                Conference on Image Analysis },
  editor    = { Salberg, Arnt-B{\o e}rre and Hardeberg, Jon Yngve and 
                Jenssen, Robert  },
  publisher = { Springer-Verlag },
  address   = { Berlin, Germany },
  isbn      = { 978-3-642-02229-6 },
  book_pages = { 783 },
  title     = { Rotation invariant image description with local binary
                pattern histogram fourier features. },
  author    = { Ahonen, Timo and
                Matas, Ji{\v r}{\'\i} and
                He, Chu and
                Pietik{\" a}inen Matti  },
  pages     = { 61--70 },
  year      = { 2009 },
  month     = { June },
  day       = { 18 },
  venue     = { Oslo, Norway },
  project   = { ICT-215078 DIPLECS },
  keywords  = { tracking, segmentation },
  annote = { In this paper, we propose Local Binary Pattern Histogram
   Fourier features (LBP-HF), a novel rotation invariant image
   descriptor computed from discrete Fourier transforms of local
   binary pattern (LBP) histograms. Unlike most other histogram based
   invariant texture descriptors which normalize rotation locally, the
   proposed invariants are constructed globally for the whole region
   to be described. In addition to being rotation invariant, the
   LBP-HF features retain the highly discrim- inative nature of LBP
   histograms. In the experiments, it is shown that these features
   outperform non-invariant and earlier version of rotation invariant
   LBP and the MR8 descriptor in texture classification, material
   categorization and face recognition tests.},
  series      = { Lecture Notes in Computer Science },
  number      = { 5575 },
}