Image Query by Texture and Color Content

Trygve Randen 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

Full paper


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.