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<p><b>Abstract</b>—We define a distance between textures for texture classification from texture features based on windowed Fourier filters. The definition of the distance relies on an interpretation of our texture attributes in terms of spectral density when the texture can be considered as a Gaussian random field. The distance between textures is then defined as a symmetrized Kullback distance which is a simple function of the attributes and does not require any normalization. An experimental analysis using Gabor filters, and in particular a comparison to quadratic distances, shows the efficiency and robustness of the method.</p>
Texture attributes and classification, windowed Fourier filters, Gabor filters, Gaussian random fields, spectral density, Kullback distance, distance between textures, segmentation of textured images.

R. Azencott, L. Younes and J. Wang, "Texture Classification Using Windowed Fourier Filters," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 19, no. , pp. 148-153, 1997.
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