Image Retrieval by Colour and Texture Using Chromaticity Histograms and Wavelet Frames
In this paper the combination of texture and colour features is used for image classification. Texture features are extracted using the Discrete Wavelet Frame analysis. 2-D or 1-D histograms of the CIE Lab chromaticity coordinates are used as colour features. The 1-D histograms of the a, b coordinates were also modeled according to the generalized Gaussian distribution. The similarity measure defined on the features distribution is based on the Bhattacharya distance. Retrieval benchmarking is performed on textured colour images from natural scenes, obtained from the VisTex database of MIT Media Laboratory and from the Corel Photo Gallery.
KeywordsTexture Feature Image Retrieval Colour Feature Wavelet Frame Classi Cation
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