Unicode-driven Deep Learning Handwritten Telugu-to-English Character Recognition and Translation System

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BV Subba Rao, Katta Subba Rao, Venkata Nagaraju Thatha, Bandi Vamsi, J. Nageswara Rao, Rajendra Kumar Ganiya


Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine. Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMS-P) and Adaptative Moment Estimation (ADAM)optimizers are used in this work to enhance the performance of U-HCR and to reduce the loss function value. This loss value reduction can be possible with optimizers by using CNN. In both online and offline datasets, proposed model showed promising results by maintaining the accuracies with 90.28% for SGD, 96.97% for RMS-P and 93.57% for ADAM respectively.

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How to Cite
BV Subba Rao, et al. (2023). Unicode-driven Deep Learning Handwritten Telugu-to-English Character Recognition and Translation System. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10), 344–359. https://doi.org/10.17762/ijritcc.v11i10.8497
Author Biography

BV Subba Rao, Katta Subba Rao, Venkata Nagaraju Thatha, Bandi Vamsi, J. Nageswara Rao, Rajendra Kumar Ganiya

BV Subba Rao1, Katta Subba Rao1, Venkata Nagaraju Thatha2, Bandi Vamsi2[0000-0001-9111-0990], J. Nageswara Rao2[ 0000-0002-2941-5379], Rajendra Kumar Ganiya3

1Dept of Information Technology, PVP Siddhartha Institute of Technology

mail: bvsrau@gmail.com

Department of Computer Science and Engineering, B V Raju Institute of Technology, Narsapur, Medak (District), Telangana, India


2Department of Information Technology

MLR INSTITUTE of technology

Hyderabad 500049


1Department of Artificial Intelligence & Data Science,

Madanapalle Institute of Technology & Science,

Madanapalle - 517326, INDIA

2Department of Computer Science and Engineering, Lakireddy Bali Reddy College of Engineering, Mylavaram, NTR District, PIN- 521230,

Andhra Pradesh, India,nagsmit@gmail.com

3Professor, Department of CSE,

Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.

E-mail: rajendragk@kluniversity.in


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