Machine Recognition of Hand Written Characters using Neural Networks

TL;DR

This paper explores how neural networks can be used to recognize handwritten characters despite variations and distortions, aiming to improve machine understanding of handwritten communication.

Contribution

It demonstrates the application of neural networks for recognizing handwritten characters, addressing challenges posed by handwriting variability and distortion.

Findings

Neural networks can effectively recognize handwritten characters.

Conversion of handwritten data into electronic form is feasible.

Neural network approach improves recognition accuracy.

Abstract

Even today in Twenty First Century Handwritten communication has its own stand and most of the times, in daily life it is globally using as means of communication and recording the information like to be shared with others. Challenges in handwritten characters recognition wholly lie in the variation and distortion of handwritten characters, since different people may use different style of handwriting, and direction to draw the same shape of the characters of their known script. This paper demonstrates the nature of handwritten characters, conversion of handwritten data into electronic data, and the neural network approach to make machine capable of recognizing hand written characters.