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