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