Comparing Intensity Transformations and Their Invariants in the Context of Color Pattern Recognition

In this paper we compare different ways of representing the photometric changes in image intensities caused by changes in illumination and viewpoint, aiming at a balance between goodness-of-fit and low complexity. We derive invariant features based on generalized color moment invariants - that can deal with geometric and photometric changes of a planar pattern - corresponding to the chosen photometric models. The geometric changes correspond to a perspective skew. We compare the photometric models also in terms of the invariants' discriminative power and classification performance in a pattern recognition system.

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