Abstract
This paper describes a color classification technique for the color subspaces definition based in 3D reconstruction approaches. These color subspaces use implicit functions to create a bounding surface that will fit a set of characteristic color samples to define a particular color. The implicit subspace reconstruction allow to define clusters of arbitrary shape for a better approximation of the color distribution, reducing misclassification problems obtained when using predefined geometrical shapes. In addition, the proposed method presents less computational complexity than methods based in color signal transformation, allowing dynamical tuning of the subspaces, and provides robustness and ease parameterization.
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Álvarez, R., Millán, E., Swain-Oropeza, R., Aceves-López, A. (2004). Color Image Classification Through Fitting of Implicit Surfaces. In: Lemaître, C., Reyes, C.A., González, J.A. (eds) Advances in Artificial Intelligence – IBERAMIA 2004. IBERAMIA 2004. Lecture Notes in Computer Science(), vol 3315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30498-2_68
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DOI: https://doi.org/10.1007/978-3-540-30498-2_68
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