DocumentCode :
3127920
Title :
Texture-based image retrieval without segmentation
Author :
Rubner, Yossi ; Tomasi, Carlo
Author_Institution :
Dept. of Comput. Sci., Stanford Univ., CA, USA
Volume :
2
fYear :
1999
fDate :
1999
Firstpage :
1018
Abstract :
Image segmentation is not only hard and unnecessary for texture-based image retrieval, but can even be harmful. Images of either individual or multiple textures are best described by distributions of spatial frequency descriptors, rather than single descriptor vectors over presegmented regions. A retrieval method based on the earth movers distance with an appropriate ground distance is shown to handle both complete and partial multi-textured queries. As an illustration, different images of the same type of animal are easily retrieved together. At the same time, animals with subtly different coats, like cheetahs and leopards, are properly distinguished
Keywords :
image retrieval; image texture; animal images; complete multi-textured queries; earth movers distance; ground distance; partial multi-textured queries; presegmented regions; spatial frequency descriptor distributions; texture-based image retrieval; Computer science; Earth; Gabor filters; Image resolution; Image retrieval; Image segmentation; Image texture; Lighting; Shape; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on
Conference_Location :
Kerkyra
Print_ISBN :
0-7695-0164-8
Type :
conf
DOI :
10.1109/ICCV.1999.790380
Filename :
790380
Link To Document :
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