DocumentCode
3539773
Title
Rotation-invariant texture Image Classification using R-transform
Author
Li, Chao-Rong ; Deng, Yong-Hai
Author_Institution
Sch. of Comput. Sci. & Eng., Univ. Electron. Sci. & Technol. of China, Chengdu, China
fYear
2012
fDate
14-15 Aug. 2012
Firstpage
271
Lastpage
274
Abstract
In this paper, An descriptor of rotation-invariant texture Image Classification is proposed. The feature exacted by using the proposed method is rotation invariant and robust to the change of spatial scale and illumination. Rotation invariant is achieved by means of Rapid transformation (R-transform) to eliminate cyclic translation resulting from rotation variation on the local circle region, which rounds a centre pixel. Combination of several descriptors with different (N, R) parameters the spatial multiscale are obtained. Texture classification experiments were carried out on the Brodatz databases and promising results are obtained from those experiments.
Keywords
feature extraction; image classification; image texture; visual databases; wavelet transforms; Brodatz database; R-transform; feature exaction; illumination; rapid transformation; rotation invariant texture image classification; Feature extraction; Histograms; Lighting; Pattern recognition; Robustness; Training; Vectors; Brodatz album; R-transform; Rotation-invariant descriptor; Texture classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on
Conference_Location
Jalarta
Print_ISBN
978-1-4673-1459-6
Type
conf
DOI
10.1109/URKE.2012.6319564
Filename
6319564
Link To Document