HANDWRITTEN ENGLISH CHARACTER RECOGNITION USING NEURAL NETWORKS

IMAGE PROCESSING

Neural Networks are being used for character recognition from last many years. This paper presents creating the Character Recognition System, in which Creating a Character Matrix and a corresponding Suitable Network Structure is key. The Feed Forward Algorithm gives insight into the enter workings of a neural network; followed by the Back Propagation Algorithm which compromises Training, Calculating Error, and Modifying Weights. We have made an attempt to recognize handwritten English characters by using a multilayer perceptron with one hidden layer. In addition, an analysis has been carried out to determine the number of hidden nodes to achieve high performance of back propagation network in the recognition of handwritten English characters. The results showed that the MLP networks trained by the error back propagation algorithm are superior in recognition accuracy and memory usage. The result indicates that the back propagation network provides good recognition accuracy of more than 70% of Handwritten English characters.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.