Color textures contain a large amount of spectral
and spatial structure that can be exploited for recognition.
Recent work has demonstrated that spatial filters
offer a convenient means of extracting illuminationinvariant
spatial information from a color image. In
this paper, we address the problem of deriving optimal
filters for illumination-invariant color texture
discrimination. Color textures are represented by a
set of illumination-invariant features that characterize
the color distribution of a filtered image region.
Given a pair of color textures, we derive a spatial filter
that maximizes the distance between these textures
in feature space. We provide a method for using the
pair-wise result to obtain a filter that maximizes discriminability
among multiple classes. A set of experim
e n t s on a database of d e t e r m i n i s t i c and r a n d o m color
textures obtained under different illumination conditions
demonstrates the improved discriminatory power
achieved by using an optimized Jilter.