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Extraction and Identification of Manipuri and Mizo Texts from Scene and Document Images

  • Loitongbam Sanayai MeeteiEmail author
  • Thoudam Doren Singh
  • Sivaji Bandyopadhyay
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11941)

Abstract

The content inside an image is exceptionally compelling. As such, text within an image can be of special interest and compared to other semantic contents, it tends to be effectively extracted. Text detection within an image is the task of detecting and localizing the portion of an image that contains the text information. Manipuri and Mizo are respectively the lingua francas of two neighboring northeastern states of Manipur and Mizoram in India. While Manipuri, is currently written using Meetei Mayek script and Bengali script, Mizo is written in Roman script with circumflex accent added to the vowels. In this work, we report the task of text detection in natural scene images and document images in Manipuri and Mizo. We made a comparative study between Maximally Stable Extremal Regions (MSER) coupled with Stroke Width Transform (SWT) and Efficient and Accurate Scene Text Detector (EAST) for the text detection. The detected text portion of both the languages is subjected to Optical Character Recognition (OCR) and a post OCR processing of spelling correction. In our experiment of the text detection, EAST outperformed the other method.

Keywords

Text detection SWT MSER EAST OCR Manipuri Mizo 

Notes

Acknowledgments

This work is supported by Scheme for Promotion of Academic and Research Collaboration (SPARC) Project Code: P995 of No: SPARC/2018-2019/119/SL(IN) under MHRD, Govt of India.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNational Institute of Technology SilcharSilcharIndia

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