This research project focuses on optimizing text visibility and enhancing document digitization from videos. Through predictive analysis, feature fusion, and advanced text recognition techniques, the project aims to improve the accuracy and efficiency of book digitization processes. Significant outcomes include the development of a comprehensive model for frame-of-interest prediction, a novel approach for feature fusion in digitization, and insights into text recognition in the context of Education 4.0.
This is a description of the dataset used in the project. It includes details about the data sources, formats, and any preprocessing steps.
Gaurav Buddhawar, Dharin Dave, Krupa Jariwala, and Chiranjoy Chattopadhyay; International Journal of Engineering, April, 2024
Gaurav Buddhawar, Krupa Jariwala, Chiranjoy Chattopadhyay; International Journal of Engineering, Vol. 37, No. 3, pp. 538-545, DOI: 10.5829/IJE.2024.37.03C.11, March, 2024
Gaurav Buddhawar, Krupa N. Jariwala, Chiranjoy Chattopadhyay; Emerging Trends in Industry 4.0 (ETI 4.0), 2021, pp. 1-5, DOI: 10.1109/ETI4.051663.2021.9619427
Gaurav Buddhawar, Dharin Dave, Krupa Jariwala, and Chiranjoy Chattopadhyay; International Conference on Soft Computing and its Engineering Applications (icSoftComp2024), 2024
Gaurav Uday Buddhawar, Jariwala Krupa, Sudeep Dilip Thepade, Chiranjoy Chattopadhyay; Mobile Stand for Document Digitization, Design No: 373169-001, Indian Patent Office, Date of Issue: 13 January 2023