Handwritten English Character Recognition Using Neural Network
نویسندگان
چکیده
In this paper, work has been performed to recognize Handwritten English Character using a multilayer perceptron with one hidden layer. The feature extracted from the handwritten character is Boundary tracing along with Fourier Descriptor. Character is identified by analyzing its shape and comparing its features that distinguishes each character. Also an analysis was carried out to determine the number of hidden layer nodes to achieve high performance of backpropagation network in the recognition of handwritten English characters. The system was trained using 500 samples of handwritings given by both male and female participants of different age groups. Test result was performed on 500 samples other than samples for training that indicates that Fourier Description combined with backpropagation network provide good recognition accuracy of 94% for handwritten English characters with less training time.
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