Fast Image Retrieval Using Color-Spatial Information.
Beng Chin Ooi, Kian-Lee Tan, Tat-Seng Chua, Wynne Hsu:
Fast Image Retrieval Using Color-Spatial Information.
VLDB J. 7(2): 115-128(1998)@article{DBLP:journals/vldb/OoiTCH98,
author = {Beng Chin Ooi and
Kian-Lee Tan and
Tat-Seng Chua and
Wynne Hsu},
title = {Fast Image Retrieval Using Color-Spatial Information},
journal = {VLDB J.},
volume = {7},
number = {2},
year = {1998},
pages = {115-128},
ee = {db/journals/vldb/OoiTCH98.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieval process.
The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image.
Two clusters from two images are similar if they are of the same color and overlap in the image space.
The number of clusters that can be extracted from an image can be very large, and it affects the accuracy of retrieval.
We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for "optimal'' performance.
To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT).
We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer discriminates clusters of different spatial locality.
We conducted an experimental study on an image database consisting of 12,000 images.
Our results show the effectiveness of the proposed color-spatial approach, and the efficiency of the proposed indexing mechanism.
Key Words
Single-colored cluster - Content-based retrieval - Color-spatial information - Sequenced multi-attribute tree
Copyright © 1998 by Springer, Berlin, Heidelberg.
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Copyright © Fri Mar 12 17:34:26 2010
by Michael Ley (ley@uni-trier.de)