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Volume: 3 | Article ID: art00032
Using Linear Models for the Illumination-Invariant Classification of Color Textures
  DOI :  10.2352/CIC.1995.3.1.art00032  Published OnlineJanuary 1995

Spatial structure in a color image can be represented using correlation functions defined within and between sensor bands. Using a linear model for surface spectral reflectance with the same number of parameters as the number of classes of photoreceptors, we show that illumination changes correspond to linear transformations of a surface correlation matrix. From this relationship, we derive a distance function for comparing sets of spatial correlation functions that can be used for illumination-invariant recognition. We demonstrate using a large body of experiments that this distance function can be used for accurate texture classification in the presence of large changes in illumination spectral distribution.

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Glenn Healey, Lizhi Wang, "Using Linear Models for the Illumination-Invariant Classification of Color Texturesin Proc. IS&T 3rd Color and Imaging Conf.,  1995,  pp 123 - 125,

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Copyright © Society for Imaging Science and Technology 1995
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