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Neural Networks for Pen Characters Recognition

This paper presents experiments that compare different kinds of features for isolated handwritten character recognition in a Neural Network environtment. The selection of valuable features is crucial in character recognition, therefore a new and meaningful set of features, the Uniform Differential Normalized Coordinates (UDNC), is introduced. These features are shown to improve the recognition rate using simple classification algorithms so they are used to train a Neural Network and test its performance on a reduced database.