Recognition of handwritten digits by image processing and neural network

Recognition of handwritten digits has been one of the first applications of neural networks. The authors propose an intermediate approach between classical methods, which are based on extraction of a small set of parameters, and pure neural methods, in which the neural network is fed with raw image data. Complexity and learning time are reduced with still good performance. Experimental results and comparisons of various parameters and classifiers, for a database of 2589 digits obtained from 30 persons are provided