  This work focuses on development of a Offline Hand Written English Character
Recognition algorithm based on Artificial Neural Network (ANN). The ANN
implemented in this work has single output neuron which shows whether the
tested character belongs to a particular cluster or not. The implementation is
carried out completely in 'C' language. Ten sets of English alphabets
(small-26, capital-26) were used to train the ANN and 5 sets of English
alphabets were used to test the network. The characters were collected from
different persons over duration of about 25 days. The algorithm was tested with
5 capital letters and 5 small letter sets. However, the result showed that the
algorithm recognized English alphabet patterns with maximum accuracy of 92.59%
and False Rejection Rate (FRR) of 0%.
