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ICPR
2000
IEEE

Robust Texture Classification by Subsets of Local Binary Patterns

8 years 9 months ago
Robust Texture Classification by Subsets of Local Binary Patterns
Recently, a nonparametric approach to texture analysis has been developed, in which the distributions of simple texture measures based on local binary patterns (LBP) are used for texture description. The basic LBP encodes 256 simple feature detectors in a single 3x3 operator. This paper shows that a properly selected subset of patterns encoded in LBP forms an efficient and robust texture description which can achieve better classification rates in comparison with the whole LBP histogram. Experiments on classification of textures from the Columbia-Utrecht (CURET) database demonstrate the robustness of the approach.
Topi Mäenpää, Timo Ojala, Matti Pie
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where ICPR
Authors Topi Mäenpää, Timo Ojala, Matti Pietikäinen, Maricor Soriano
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