Improved Real time Signboard Detection and Translation Using FRCNN

Dona Lal, Jothika Mohan, S. RenjishaT, Saviya Davis, Divya Mohan
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Abstract

In India, majority of people are speaking the language Hindi, but a major portion of signboards are in English. On a business or pleasure trip, the travelers get confused by the various sign boards written in English. As smartphones becomes most popular inrecent years,they canrely on smartphone for the same. This paper explains the work intended to build a mobile application that can recognize the English content and sign present on the signboard image, detect and translate the content and symbols from English to Hindi and display the translated Hindi text back to the screen of the phone. The system uses pre-trained faster regional convolutional neural networkusing pre-trained CNN for object detection, tesseract OCR for text extraction and English-to-Hindi dictionary for translation.
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改进的基于FRCNN的实时广告牌检测和翻译
在印度,大多数人说印地语,但大部分招牌都是英文的。在商务或观光旅行中,旅行者会被各种用英语写的告示牌弄糊涂。随着近年来智能手机变得越来越流行,他们可以依靠智能手机来做同样的事情。本文解释了旨在构建一个移动应用程序的工作,该应用程序可以识别标识图像上的英语内容和符号,检测并翻译从英语到印地语的内容和符号,并将翻译后的印地语文本显示回手机屏幕。该系统使用预训练的更快的区域卷积神经网络,使用预训练的CNN进行对象检测,使用tesseract OCR进行文本提取,使用英语到印地语字典进行翻译。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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