Comprehensive study of deep learning based Telugu OCR: A survey

M. V. Vijaya Saradhi; K. Rakesh; D. Ravi Prasanna; K. Swetha; B. Prawin

doi:10.30574/ijsra.2023.8.1.0050

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Comprehensive study of deep learning based Telugu OCR: A survey

M. V. Vijaya Saradhi, K. Rakesh ^*, D. Ravi Prasanna, K. Swetha and B. Prawin

Department of Computer Science and Engineering, ACE Engineering College, Hyderabad, Telangana, India.

Research Article

International Journal of Science and Research Archive, 2023, 08(01), 353-356.
Article DOI: 10.30574/ijsra.2023.8.1.0050
DOI url: https://doi.org/10.30574/ijsra.2023.8.1.0050

Publication history

Received on 03 December 2022; revised on 14 January 2023; accepted on 17 January 2023

Abstract

There will be no computer-editable text in the image file. The method of optical character recognition (OCR), which can read handwritten or printed text in images, turns that text into a file that can be edited on a computer. English has a well-developed OCR system. OCR is currently required for Indian languages in order to process application forms, categorise books in libraries, and preserve historical records that are mostly written in Indian languages. The Telugu language presents challenges for OCR since each character is made up of a single consonant, a single vowel, or a compound of vowels and consonants.

Keywords

Text segmentation; Text Extraction; Image-based; Document processing; Convolution Neural Network; OCR

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How to cite this article

M. V. Vijaya Saradhi, K. Rakesh, D. Ravi Prasanna, K. Swetha and B. Prawin. Comprehensive study of deep learning based Telugu OCR: A survey. International Journal of Science and Research Archive, 2023, 08(01), 353-356. Article DOI: https://doi.org/10.30574/ijsra.2023.8.1.0050

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