Abstract
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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Mindru, F., Moons, T., Van Gool, L. (2002). Comparing Intensity Transformations and Their Invariants in the Context of Color Pattern Recognition. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47979-1_30
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DOI: https://doi.org/10.1007/3-540-47979-1_30
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