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Chinese Character Translator on Mobile Phone using Optical Character Recognition and Bing Translator API

Handojo, Andreas and Purbowo, Anita Nathania and BUDIONO, FENNY VALENTINE (2020) Chinese Character Translator on Mobile Phone using Optical Character Recognition and Bing Translator API. [UNSPECIFIED]

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      Official URL: http://wcse.us/

      Abstract

      Chinese language is one of the international languages whose have users almost 35% of the worlds population. Nonetheless the Chinese language has problems in learning how to write and how to read because it is in the form of characters or symbols so that it is more difficult to learn it. Chinese characters that used today is simplified Chinese character with approximately 3000 common characters that daily used. This character / symbol can also be written in Latin alphabet form called hanzi / hanyu pinyin. Some application developers such as Yellow Bridge, Google, Qhanzi, and Bing have provided translator applications from the Chinese characters to the Latin alphabet and vice versa. The application provided is generally still web-based and does not involve the ability to input the shape of a Chinese character in the form of an image, for example image input either from a file or directly from a camera input. This research try to build a Chinese character translator application using Tesseract Optical Character Recognition (OCR) Engine to retrieve the Chinese characters from the image, then translate it using a translator on the Bing API. This application will running on mobile phone. So the user could use image or mobile phone camera as an input. The test results show that the application can operate on various Android devices. OCR Engine has been able to perform the translation function with 74% success rate. The input image could have tolerance angle of approximately 15 degrees.

      Item Type: UNSPECIFIED
      Subjects: Q Science > QA Mathematics > QA76 Computer software
      Divisions: Faculty of Industrial Technology > Informatics Engineering Department
      Depositing User: Admin
      Date Deposited: 18 Mar 2020 21:27
      Last Modified: 15 Sep 2020 22:52
      URI: https://repository.petra.ac.id/id/eprint/19452

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