Alpha-Numeric Character Recognition for Blinds Using Deep-Learning Techniques

Abstract

In this study, we are introducing an alphanumeric character recognition system using Deep Learning concepts. This system will classify Alphabets and Numeric characters with high accuracy. Identification and classification of characters would be essential for users with who have problem reading the characters in a document or any other text-based media. We utilize a dataset containing of letters A to Z with a total of 3,89,765 images which is approximately 15000 images per Alphabet. We classify the characters based on the shape of each character and using Deep Learning concepts like CNN, RNN and Random Forest architecture to train out the dataset and develop a system which produces the highest accuracy. The success rate in identifying the characters makes it a very easy and an efficient tool.