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SCIA
2009
Springer

Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features

10 years 1 months ago
Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features
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 discriminative 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.
Timo Ahonen, Jiri Matas, Chu He, Matti Pietikä
Added 27 May 2010
Updated 27 May 2010
Type Conference
Year 2009
Where SCIA
Authors Timo Ahonen, Jiri Matas, Chu He, Matti Pietikäinen
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