A Novel Approach for Optical Character Recognition (OCR) of Handwritten Telugu Alphabets using Convolutional Neural Networks

Telugu is a South Indian language that more than 10 Crore people spoke in this world. The alphabets of the Telugu language are more complex, alpha-syllabary, and agglutinative in nature. Different alphabets are like each other and will overlap with other alphabets. Due to its core, the handwritten alphabets in the images cannot be detected easily by the existing optical character recognition system. Our project will create a dataset of various representations of Telugu alphabets to avoid these problems. The proposed system can be trained to detect the character present in the images. This paper proposes a new technique to identify the handwritten alphabets of Telugu language in the pictures by using a Deep Convolutional Neural Network. A remarkable improvement has been achieved by recognizing the individual alphabets with an overall accuracy of 80% - 95% with the proposed model.