OCR of Kannada Characters Using Deep Learning

Abstract

Kannada, A dravidian language of south India that consists of kannada numerals from 0 to 9 and 49 letters that are further classified into swara, vyanjana and yogavahagalu. The task Optical Character Recognition(OCR) is to transform printed or handwritten text into digital form. This technique can be explored to extract kannada numerals and letters from images of handwritten documents, processed using image processing techniques such as segmentation, skewing and slanting using OpenCV. Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Convolutional neural network(CNN) is a deep learning technique that can be used to train the model and classify kannada characters using Tensorflow and Keras. Our study has showed that our model has outperformed present methods to classify Kannada numerals and characters with 100% accuracy.