Rotation-invariant features for texture image classification

被引：0
|
作者：
Jalil, A. [1 ]
Qureshi, I. M. [1 ]
Manzar, A. [1 ]
Zahoor, R. A. [1 ]
机构：
[1] Muhammad Ali Jinnah Univ, Islamabad Campus, Islamabad, Pakistan
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON ENGINEERING OF INTELLIGENT SYSTEMS | 2006年
关键词：
rotation invariant; texture analysis; principal component analysis; wavelet transform;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Texture features based on wavelet transform are sensitive to texture rotation and translation.. This paper develops a new rotation invariant texture analysis technique using Principal Components Analysis (PCA) and wavelet transform. The PCA is first used to calculate the angle of the principal direction of the texture. Then, the texture is rotated in the opposite direction by the same angle as detected by PCA. Finally a wavelet transform is applied to the preprocessed texture to extract features which are rotation invariant.
引用
收藏
页码：42 / +
页数：3
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