AUGMENTED REALITY BASED REAL TIME LANGUAGE TRANSLATION SYSTEM
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Date
2025
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Publisher
NHCE
Abstract
One new area that has a lot of potential for removing language barriers is real-time language translation. Optical character recognition (OCR), natural language processing (NLP), and live video processing are all combined into one seamless application in this project's real-time language translation system. The program offers an interactive, user-friendly platform for text detection and translation in live video streams and was created with Flask, Paddle OCR, Google Translator API, OpenCV, and PostgreSQL. In real-world situations, such as signboards, documents, or any textual content recorded by a camera, the technology seeks to help people comprehend foreign writing.
Developing a real-time language translation system that can identify text in live video streams, translate it into a target language, and superimpose the translated text on the video is the aim of this project. User authentication, text detection, OCR, translation, live video processing, and database connectivity are all included in the modular system. Every part functions in unison to deliver precise and effective translations in real time, guaranteeing user interaction and usability.
The architecture of the system is designed to manage several tasks. First, secure application access is guaranteed by the user authentication module, which is implemented with Flask and PostgreSQL. In addition to choosing their preferred source and destination languages, users can register and log in. Next, PaddleOCR uses bounding boxes to identify text sections in live video frames. Next, the Google Translator API receives the identified text and begins translating it. Pillow is used to display the translated text over the video feed, while OpenCV makes sure that live video processing runs smoothly.