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Character recognition using tesseract enabling multilingualism.

Niharika, Gorsa Lakshmi; Bano, Shahana; Kumar, Pavuluri Shyam; Deepika, Tinnavalli; Thumati, Hampi


Gorsa Lakshmi Niharika

Pavuluri Shyam Kumar

Tinnavalli Deepika

Hampi Thumati


Character recognition builds a recognizing factor for identifying the accuracy in characters. The accuracy of classifying the recognizing characters in an image is applied through deep learning methods. The character recognition is mainly focusing on the layers of text recognition through deep learning techniques. Well cleared python code assists to furnish all the levels of image by following deep learning that algorithmically analyse and recognize text from the given input image. This research work has been proposed for recognizing characters using deep learning techniques and recognize the input image with well-furnished and most efficient output. It provides a high level of accuracy-built output after the recognition of characters in the high-resolution image. This recognized character can be converted into user desired languages where the proposed model is trained to recognize some particular languages.


NIHARIKA, G.L, BANO, S., KUMAR, P.S., DEEPIKA, T. and THUMATI, H. 2020. Character recognition using tesseract enabling multilingualism. In Proceedings of the 4th International conference on electronics, communication and aerospace technology (ICECA 2020), 5-7 November 2020, Coimbatore, India. Piscataway: IEEE [online], pages 1321-1327. Available from:

Conference Name 4th International conference on electronics, communication and aerospace technology (ICECA 2020)
Conference Location Coimbatore, India
Start Date Nov 5, 2020
End Date Nov 7, 2020
Acceptance Date Oct 7, 2020
Online Publication Date Dec 28, 2020
Publication Date Dec 31, 2020
Deposit Date Sep 20, 2023
Publicly Available Date Sep 20, 2023
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 1321-1327
ISBN 9781728163888
Keywords Character recognition; Image processing; Deep learning; Machine learning
Public URL


NIHARIKA 2020 Character recognition using (AAM) (591 Kb)

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