A neuro-fuzzy approach to recognize Arabic handwritten characters
Adel M. Alimi · Proceedings of International Conference on Neural Networks (ICNN'97) · 2002
In this paper we describe a system that recognizes online Arabic handwritten characters. In this system, a fuzzy neural network is used to classify characters. The characters used in this system were segmented from cursive handwriting that are modelled by a theory of movement generation. Based on this theory, the features extracted from each character are the neuro-physiological parameters of the equation describing the curvilinear velocity of the script. For each character presented to the system, a fuzzy membership is assigned to each output of the neural network.