DocumentCode :
1885662
Title :
Contourlet Retrieval System Using Absolute Mean and Kurtosis Features
Author :
Chen, Xin-Wu ; Liu, Yu-Xi
Author_Institution :
Coll. of Phys. & Electron., Xinyang Normal Univ., Xinyang, China
fYear :
2010
fDate :
25-26 Dec. 2010
Firstpage :
1
Lastpage :
4
Abstract :
To improve the retrieval rate of contourlet transform retrieval system,a new contourlet retrieval system was proposed.The feature vectors were constructed by cascading the absolute mean energy and kurtosis of each sub-band contourlet coefficients and the similarity measure used here is Canberra distance. Experimental results on 109 brodatz texture images show that using the features cascaded by absolute mean and kurtosis can lead to a higher retrieval rate than the combination of standard deviation and absolute mean which is most commonly used today under same dimension of feature vectors.
Keywords :
image retrieval; image texture; transforms; Canberra distance; absolute mean energy; contourlet transform retrieval system; feature vectors; kurtosis features; standard deviation; Energy measurement; Feature extraction; Image retrieval; Manganese; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location :
Wuhan
ISSN :
2156-7379
Print_ISBN :
978-1-4244-7939-9
Electronic_ISBN :
2156-7379
Type :
conf
DOI :
10.1109/ICIECS.2010.5677689
Filename :
5677689
Link To Document :
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