Illumination-Invariant Recognition of Texture in Color Images
G. Healey and L. Wang
We represent texture in a color image using spatial correlation functions
defined within and between sensor bands. This representation has been
shown to be useful for surface recognition, but the structure of spatial
correlation functions depends on the spectral properties of the scene
illumination. 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. This distance
function can be computed efficiently from estimated correlation functions.
We demonstrate using a large body of experiments that this distance
function can be used for accurate surface recognition in the presence of
large changes in illumination spectral distribution.
Back to the ICVL homepage