Image Transliteration from Vernacular Languages

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Image Transliteration from Vernacular Languages

Gupta, Yogesh / Saraswat, Amit / Raghuwanshi, Ghanshyam

India is a multi-cultured and multi-language country, which has 23 official languages, and Hindi is known as the mother language as most of the people speak Hindi here. This paper implements a model which can extract text from images and then transliterates the text written from Indic language (Hindi) to English language. It presents distinctive issues of various text styles and patterns, comparability in structure. Therefore, it is essential to discover viable techniques for text extraction. It can be useful for a tourist to easily read the signboards or names of shops in North India as the focus of this work is to work on Hindi language. A great deal of enhancements has been made in the field deep learning and natural learning processing. This paper implements text extraction and transliteration in an efficient manner by using approaches which provide accurate results. Google Vision API and natural language processing have been used for text extraction and performing transliteration, respectively, in this paper.

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Document information

Title :

Image Transliteration from Vernacular Languages

Additional title:

Lect. Notes Electrical Eng.

Contributors:

Dwivedi, Sanjeet (editor) / Singh, Sanjeev (editor) / Tiwari, Manish (editor) / Shrivastava, Ashish (editor) / Gupta, Yogesh (author) / Saraswat, Amit (author) / Raghuwanshi, Ghanshyam (author)

Published in:

Flexible Electronics for Electric Vehicles ; Chapter : 23 ; 227-234

Lecture Notes in Electrical Engineering ; 863

Publication date :

2022-10-05

Size :

8 pages

ISBN :

978-981-19-0588-9 , 978-981-19-0587-2

ISSN :

1876-1119 , 1876-1100

DOI :