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 :
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