Texture classification using invariant features of local textures

被引:6
|
作者
Janney, P. [1 ]
Geers, G. [2 ]
机构
[1] Univ New S Wales, Sch Engn & Comp Sci, Sydney, NSW 2032, Australia
[2] NICTA, Sydney, NSW 2032, Australia
基金
澳大利亚研究理事会;
关键词
D O I
10.1049/iet-ipr.2008.0229
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the authors present a texture descriptor algorithm called invariant features of local textures (IFLT). IFLT generates scale, rotation and (essentially) illumination invariant descriptors from a small neighbourhood of pixels around a centre pixel or a texture patch. Texture classification experiments were carried out on the Brodatz, Outex and KTH-TIPS2 databases. Demonstrated texture classification accuracy exceeds the previously published state of the art at a significantly lower computational cost. Experiments also suggests that IFLT descriptors are in a sense intuitive texture descriptors.
引用
收藏
页码:158 / 171
页数:14
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