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

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.