Segmentation based on color, instead of intensity only, pro- vides an easier distinction between materials, on the condition
that ro- bustness against irrelevant parameters is achieved, such as illumination source, shadows, geometry and camera sensitivities.
Modeling the phys- ical process of the image formation provides insight into the effect of different parameters on object
color.
In this paper, a color differential geometry approach is used to detect material edges, invariant with respect to illumination
color and imaging conditions. The performance of the color invariants is demonstrated by some real-world examples, showing
the invariants to be successful in discounting shadow edges and illumination color.