Handwritten Character Recognition: Training a Simple NN for Classification Using MATLAB

In this paper, we identify handwritten characters with the use of neural networks. We have to construct suitable neural network and train it properly. The program is able to extract the characters one by one and map the target output for training purpose. After automatic processing of the image, the training dataset has to be used to train for recognition purpose. The proposed method is based on the use of feed forward back propagation method to classify the characters. The ANN is trained using the Back Propagation algorithm. In the proposed system, numerical digits and alphabets are represented that are used as input then they are fed to an ANN. Neural network followed by the Back Propagation Algorithm which compromises Training. The program code is written in MATLAB and supported with the usage of Graphical User Interface (GUI).