Handwritten Telugu Character Recognition Using Machine Learning

Title

Handwritten Telugu Character Recognition Using Machine Learning

Creator

Karapu B.M.; Anoop G.L.; Elappila M.; Mithun B.N.

Description

The Telugu language is the most prominent representative within the Dravidian language family, predominantly spoken in the southeastern regions of India. Handwritten character recognition in Telugu has significant applications across diverse fields such as healthcare, administration, education, and paleography. Despite its importance, the Telugu script differs significantly from English, presenting distinct challenges in recognizing characters due to its complexity and diverse character shapes. This study explores the application of machine learning, particularly delving into deep learning techniques, to improve the accuracy of Telugu character recognition. This paper proposes a model to recognize handwritten Telugu characters using Convolutional Neural Network (CNN). The proposed study demonstrates the accuracy in identifying diverse handwritten Telugu characters. We assess the system's performance against conventional and machine learning methodologies and preprocess an extensive dataset to guarantee strong model training. The proposed model excels in accurately predicting visually similar but distinct characters, achieving an impressive accuracy rate of 96.96%. 2024 IEEE.

Source

International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

character recognition; Convolutional Neural Network (CNN); Handwritten Telugu character recognition

Coverage

Karapu B.M., Christ Deemed to Be University, Department of Computer Science & Engineering, Bengaluru, India; Anoop G.L., Christ Deemed to Be University, Department of Computer Science & Engineering, Bengaluru, India; Elappila M., Christ Deemed to Be University, Department of Computer Science & Engineering, Bengaluru, India; Mithun B.N., Christ Deemed to Be University, Department of Computer Science & Engineering, Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 979-835038295-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICDCOT61034.2024.10515646

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193214691&doi=10.1109%2fICDCOT61034.2024.10515646&partnerID=40&md5=dfad9be0ae1f665520883bb30e949189