DocumentCode :
2292566
Title :
Adaptive texture image retrieval in transform domain
Author :
Zhang, Bin ; Tomai, C.I. ; Aidong Zhang
Author_Institution :
Comput. Sci. & Eng. Dept., State Univ. of New York at Buffalo, Amherst, MA, USA
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
401
Abstract :
A large number of algorithms have been proposed to retrieve and analyze texture images. While much effort has been made to find algorithms applicable to all textures for superior retrieval performance, less work has been done to adaptively integrate various texture retrieval and analysis algorithms. As no individual texture retrieval algorithm is suited for every texture category, a hybrid scheme would outperform any individual method. In this paper, an adaptive retrieval scheme (ARS) for texture image indexing is proposed to dynamically adapt different transforms to different texture patterns for better retrieval performance. The experiments on the Brodatz texture database show that ARS significantly outperforms any individual transform.
Keywords :
adaptive filters; database indexing; feature extraction; image retrieval; image texture; transforms; Brodatz texture database; adaptive integration; adaptive retrieval scheme; dynamic adaptation; hybrid scheme; retrieval performance; texture image indexing; texture patterns; transform domain; Algorithm design and analysis; Discrete cosine transforms; Gabor filters; Image analysis; Image databases; Image retrieval; Image texture analysis; Performance analysis; Spatial databases; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7304-9
Type :
conf
DOI :
10.1109/ICME.2002.1035622
Filename :
1035622
Link To Document :
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