An efficient low-dimensional color indexing scheme
for region based image retrieval

Yining Deng and B. S.Manjunath
Department of Electircal and Computer Engineering
University of California, Santa Barbara, CA 93106-9560
deng@iplab.ece.ucsb.edu, manj@ece.ucsb.edu
 

Abstract

In this work, an efficient low-dimensional color indexing
scheme for region-based image retrieval is presented. The colors
in each image region are first quantized so that only a small number
of cluster centroids are needed to represent the region color
information. The proposed color feature descriptor consists of
these quantized colors and their percentages in the region. A similarity
distance measure is defined and shown to be equivalent to
the quadratic color histogram distance measure. The quantized
colors are indexed in the 3-D color space so that high-dimensional
indexing can be avoided. During the search process, each
quantized color in the query is used as a separate cue to find
matches containing that color. The matches from all the query
colors are then joined to obtain the final retrievals. Experimental
results show that the proposed scheme is fast and accurate compared
to the color histogram approach.