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

机译:从场景和文档图像中提取和识别Manipuri和Mizo文本

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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.
机译:图像内的内容特别引人注目。这样,图像内的文本可能会特别令人感兴趣,并且可以与其他语义内容进行比较。倾向于被有效地提取。图像内的文本检测是检测和定位包含文本信息的图像部分的任务。 Manipuri和Mizo分别是印度Manipur和Mizoram的两个相邻东北邦的通用语。目前,Manipuri是使用Meetei Mayek脚本和孟加拉语脚本编写的,而Mizo是用罗马字母编写的,并在元音中添加了抑扬音符号。在这项工作中,我们报告了Manipuri和Mizo中自然场景图像和文档图像中文本检测的任务。我们对最大稳定的末端区域(MSER)与笔划宽度变换(SWT)和高效准确的场景文本检测器(EAST)进行文本检测之间进行了比较研究。 '检测到的两种语言的文本部分均经过光学字符识别(OCR)和OCR后的拼写校正处理。在我们的文本检测实验中,EAST优于其他方法。

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