Hand Written Character Recognition System

Hand written character recognition is one of the focused areas of research in the field of Artificial intelligence. An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. The Modules of this project are.  Neuron creation – This module involves creating an artificial neuron and developing a multi layered neural network.  ANN & Controls component – This module involves developing an algorithm to scan, filter and make ANN learn about the hand written code. This is the module that is responsible for pattern searching and matching functionality.  Online Character Recognition component– This module involves creating a Windows application with graphical user interface components to configure neural network, to carryout learning process and to enable it to detect the hand written characters.