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Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

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A benchmark dataset for printed Meitei/Meetei script character recognition.

Yanglem Loijing Khomba Khuman¹, Salam Dickeeta Devi¹, Ch Ponykumar Singh¹

¹Department of Computer Science, Manipur University, India.

|November 25, 2022

Summary

This summary is machine-generated.

A new dataset of Manipuri (Meitei) script printed documents is now available. This resource supports optical character recognition (OCR) and natural language processing (NLP) research for the Tibeto-Burman language.

Keywords:

Meitei/Meetei script Natural language processing Optical character recognition Printed document images

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Area of Science:

Linguistics
Computer Science
Information Science

Background:

The Manipuri language, also known as Meitei, is the official language of Manipur, India.
It belongs to the Tibeto-Burman language family.
A lack of comprehensive datasets has hindered research in optical character recognition (OCR) and natural language processing (NLP) for this script.

Purpose of the Study:

To introduce a benchmark dataset of printed Manipuri (Meitei) script document images.
To facilitate research and development in OCR and NLP for the Manipuri language.

Main Methods:

Compilation of 824 pages of printed Manipuri documents.
Generation of binarized images, text files, and XML files for each page.
Extraction and categorization of 51,460 isolated character samples (consonants, half-consonants, vowels, numerals).

Main Results:

A comprehensive dataset comprising raw and processed document images.
A detailed character sample set with 27 consonants, 7 half-consonants, 8 vowels, and 10 numerical characters.
The dataset is structured for easy integration into OCR and NLP research pipelines.

Conclusions:

The presented dataset serves as a valuable resource for advancing OCR and NLP technologies for the Manipuri language.
It provides a foundation for developing more accurate and efficient systems for processing Manipuri script.
This initiative supports the preservation and digital accessibility of the Manipuri language.