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In this paper we present an invariant statistical approach to classifying red blood cells (RBC). Given a database of 5062 grayscale images, we model the distribution of the observations by using Gaus-sian mixture densities within a Bayesian framework. As invariance is of great importance when classifying RBC, we use a Fourier-Mellin based approach to(More)
In this paper we present an invariant statistical approach to classifying red blood cells (RBC). Given a database of 5062 grayscale images, we model the distribution of the observations by using Gaus-sian mixture densities within a Bayesian framework. As invariance is of great importance when classifying RBC, we use a Fourier-Mellin based approach to(More)
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