Image Query by Texture and Color Content
and John Håkon Husøy
Høgskolen i Stavanger
P.O. Box 2557 Ullandhaug, N-4004 Stavanger, Norway
In Proc. IEEE International Conference on Image Processing.
Santa Barbara, CA, October 1997
In this paper, a new scheme for color and texture feature extraction
for image content search is presented.
We introduce a scheme using the two chrominance components for color
information and an computationally efficient infinite impulse
response (IIR) quadrature mirror filter bank (QMF) energy measure of
the luminance component for texture information.
The color and texture information is combined into one feature vector,
and the components are balanced with respect to dimensionality.
We illustrate the utility of our features with experiments searching
for a specific color texture in a large database of images.
Several different sub-band decompositions are evaluated.
Features extracted using a previously published Gabor filter bank
are also evaluated against the proposed scheme.
We conclude that the proposed scheme outperforms the Gabor features
in both quality and complexity.