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In the pattern recognition area, one of the most important tasks is the ability of a neural network to classify objects regardless of affine transformations. Contoured objects can be described with Bezier curves and the description is affine transformation invariant. Direct use of the curves for a neural network input isn't applicable because it's possible that descriptions of the same objects consist of different number of Bezier curves. We propose histogram coding, decomposing a list of Bezier curves, which can be used as an input for a neural network. Experiments show that proposed coding gives good results to solve formulated problem.