ItemConference Paper

Real-Time Video Text Spotting with OpenCV and OCR Powered by Deep Learning

Title
Real-Time Video Text Spotting with OpenCV and OCR Powered by Deep Learning
Creator
Mary, Sahaaya Arul; Dakshinamurthi, Vidyabharathi; Tamilselvi, M.; Seshaiah, M.A.; Abinaya, A.; Syed Husain, S.
Description
The identification of text in video places huge challenges, and translating them into target form demands high-level expert skills in computer vision and deep learning. This system can grab and supervise the real-time video process of text elements by utilizing OpenCV for text recognition and extraction. The proposed model was employed diverse machine translation models to guarantee high-quality results for translation. Based on wide testing and assessment, the goal is to make the apporach fast and precise, offering valuable tool for instructors, content creators, and overall users. This novel approach solves problems relating to language difficulty problems. Key elements include video processing, text detection and recognition, and machine translation. In addition to these essential functionalities, sophisticated preprocessing methods are applied to make text stand out from diverse backgrounds to render high performance in diverse environments. Deep learning algorithms improves the accuracy of text detection, especially for occluded or distorted characters. Finally, the cloud-based translation service offers real-time multilingual support to enable maximal adaptability to user needs. For the first time, this innovative technology finally enables streamlining access to the content and facilitates cross-cultural communication in multimedia contexts with nigh-guaranteed linguistic barriers broken down. 2025 IEEE.
Source
2025 IEEE 6th Global Conference for Advancement in Technology, GCAT 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
OpenCV; Real-Time Processing; Video Processing Text Detection
Coverage
Mary S.A., Christ University, School of Engineering and Technology, Department of Aiml & Data Science, Karnataka, Bangalore, India; Dakshinamurthi V., Sona College of Technology, Department of Computer Science and Engineering, Salem, India; Tamilselvi M., Roever Engineering College, Department of Computer Science and Engineering, Tamilnadu, Perambalur, India; Seshaiah M.A., Velammal Engineering College, Department of Ece, Surapet, Chennai, India; Abinaya A., Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology, Department of Ece, Avadi, Tamilnadu, Chennai, India; Syed Husain S., K. Ramakrishnan College of Engineering, Dept. of Ece, Tamil Nadu, Tiruchirappalli, 621112, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833151458-7;
Format
online
Language
English
Type
Conference paper

Citation

Mary, Sahaaya Arul; Dakshinamurthi, Vidyabharathi; Tamilselvi, M.; Seshaiah, M.A.; Abinaya, A.; Syed Husain, S., “Real-Time Video Text Spotting with OpenCV and OCR Powered by Deep Learning,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25842.

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