Image Content Search by Color and Texture Properties
نویسندگان
چکیده
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 a computationally eecient innnite impulse response (IIR) quadrature mirror lter 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 dimen-sionality. We illustrate the utility of our features with experiments in searching for a speciic color texture in a large database of images. Several diierent sub-band decompositions are evaluated. Features extracted using a previously published Gabor lter bank are also evaluated against the proposed scheme. We conclude that the proposed scheme outperforms the Gabor features in both quality and complexity.
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