Machine Recognition of Hand Written Characters using Neural Networks
This work addresses the challenge of automating handwritten character recognition for general communication and data recording, but it appears incremental as it applies existing neural network methods without claiming specific improvements.
The paper tackles the problem of recognizing handwritten characters by addressing variations in handwriting styles and distortions, using a neural network approach to convert handwritten data into electronic form.
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.