Sciweavers

Share
ICIP
2010
IEEE

Rotation invariant texture classification using adaptive LBP with directional statistical features

9 years 6 months ago
Rotation invariant texture classification using adaptive LBP with directional statistical features
Local Binary Pattern (LBP) has been widely used in texture classification because of its simplicity and computational efficiency. Traditional LBP codes the sign of the local difference and uses the histogram of the binary code to model the given image. However, the directional statistical information is ignored in LBP. In this paper, some directional statistical features, specifically the mean and standard deviation of the local absolute difference are extracted and used to improve the LBP classification efficiency. In addition, the least square estimation is used to adaptively minimize the local difference for more stable directional statistical features, and we call this scheme the adaptive LBP (ALBP). By coupling the directional statistical features with ALBP, a new rotation invariant texture classification method is presented. Experiments on a large texture database show that the proposed texture feature extraction and classification scheme could significantly improve the classifi...
Zhenhua Guo, Lei Zhang, David Zhang, Su Zhang
Added 12 Feb 2011
Updated 12 Feb 2011
Type Journal
Year 2010
Where ICIP
Authors Zhenhua Guo, Lei Zhang, David Zhang, Su Zhang
Comments (0)
books