  A novel, generic scheme for off-line handwritten English alphabets character
images is proposed. The advantage of the technique is that it can be applied in
a generic manner to different applications and is expected to perform better in
uncertain and noisy environments. The recognition scheme is using a multilayer
perceptron(MLP) neural networks. The system was trained and tested on a
database of 300 samples of handwritten characters. For improved generalization
and to avoid overtraining, the whole available dataset has been divided into
two subsets: training set and test set. We achieved 99.10% and 94.15% correct
recognition rates on training and test sets respectively. The purposed scheme
is robust with respect to various writing styles and size as well as presence
of considerable noise.
