DocumentCode :
1978292
Title :
Contourlet-Based Feature Extraction on Texture Images
Author :
Yifan, Zhao ; Liangzheng, Xia
Author_Institution :
Sch. of Autom., Southeast Univ., Nanjing, China
Volume :
6
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
221
Lastpage :
224
Abstract :
According to the directional property and coefficients energy feature in contourlet decomposition, we proposed a new algorithm which is adapted to extract the rotated texture¿s features. By using this algorithm, we can take good advantage of directional information in contourlet decomposition by different decomposition level. With the extracted feature vectors, we can easily distinguish different texture in standard Brodatz texture database with high classification accuracy.
Keywords :
feature extraction; image classification; image texture; Brodatz texture database; contourlet decomposition; contourlet-based feature extraction; feature vector extraction; image classification accuracy; texture images; Automation; Band pass filters; Data mining; Discrete wavelet transforms; Feature extraction; Filter bank; Image edge detection; Low pass filters; Signal processing algorithms; Wavelet transforms; contourlet; rotation; texture; wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.364
Filename :
4723236
Link To Document :
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