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