DocumentCode :
2852754
Title :
Improving image retrieval performance by using both color and texture features
Author :
Zhang, Dengsheng
Author_Institution :
Gippsland Sch. of Comput. & Inf., Tech. Monash Univ., Churchill, Vic., Australia
fYear :
2004
fDate :
18-20 Dec. 2004
Firstpage :
172
Lastpage :
175
Abstract :
Most content-based image retrievals (CBIR) use color as image features. However, image retrieval using color features often gives disappointing results because in many cases, images with similar colors do not have similar content. Color methods incorporating spatial information have been proposed to solve this problem, however, these methods often result in very high dimensions of features which drastically slow down the retrieval speed. In this paper, a method combining both color and texture features of image is proposed to improve the retrieval performance. Given a query, images in the database are firstly ranked using color features. Then, the top ranked images are re-ranked according to their texture features. Results show the second process improves retrieval performance significantly.
Keywords :
content-based retrieval; image colour analysis; image retrieval; image texture; content-based image retrieval; image texture; Australia; Content based retrieval; Feature extraction; Histograms; Image databases; Image retrieval; Information retrieval; Robustness; Shape; Spatial databases; CBIR; color; image retrieval; texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Graphics (ICIG'04), Third International Conference on
Conference_Location :
Hong Kong, China
Print_ISBN :
0-7695-2244-0
Type :
conf
DOI :
10.1109/ICIG.2004.86
Filename :
1410413
Link To Document :
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