Open access Jurnal SINTA 1
Handwritten text recognition system using Raspberry Pi with OpenCV TensorFlow
International Journal of Electrical and Computer Engineering (IJECE) · Vol. 15 No. 2 (2025)
- ISSN
- 2722-2578, 2088-8708
- Published
- 2025-04-01
- Publisher
- Institute of Advanced Engineering and Science
Abstract
Handwritten text recognition (HTR) technology has brought about a revolution in the way handwritten data is converted and analyzed. This proposed work focuses on developing a HTR system using deep learning through advanced deep learning architecture and techniques. The aim is to create a model for real-time analysis and detection of handwritten texts. The proposed deep learning architecture that is convolutional neural networks (CNNs), is investigated and implemented with tools like OpenCV and TensorFlow. The model is trained on large handwritten datasets to enhance recognition accuracy. The system’s performance is evaluated based on accuracy, precision, real-time capabilities, and potential for deployment on platforms like Raspberry Pi. The actual outcome is a robust HTR system that can convert handwritten text to digital formats accurately. The developed system has achieved a high accuracy rate of 91.58% in recognizing English alphabets and digits and outperformed other models with 81.77% mAP, 78.85% precision, 79.32% recall, 79.46% F1-Score, and 82.4% receiver operating characteristic (ROC). This research contributes to the advancement of HTR technology by enhancing its precision and utility.
Collaboration network of the authors
26 authors · 71 co-authorship links · 35 across different organisations
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Universiti Teknikal Malaysia Melaka
- Rabdan Academy
- National University Zaporizhzhia Polytechnic
- Lviv Polytechnic National University
- National University of Malaysia
- International Islamic University Malaysia
- Universitas Ahmad Dahlan
- Other organisations
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Mohd Faizal Yusof | Rabdan Academy | 2 |
| Tole Sutikno | Universitas Ahmad Dahlan | 1 |
| Mohd Hatta Jopri | Universiti Teknikal Malaysia Melaka | 1 |
| Mustafa Manap | Universiti Teknikal Malaysia Melaka | 1 |
| A. K. M. Zakir Hossain | Universiti Teknikal Malaysia Melaka | 1 |
| Muhammad Ibn Ibrahimy | International Islamic University Malaysia | 1 |
| Nataliia Lotoshynska | Lviv Polytechnic National University | 1 |
| Solomiya Popova | Lviv Polytechnic National University | 1 |
| Irianto Irianto | Rabdan Academy | 1 |
| Ievgen Fedorchenko | National University Zaporizhzhia Polytechnic | 1 |
| Andrii Oliinyk | Affiliation unknown | 1 |
| Maksym Chornobuk | National University Zaporizhzhia Polytechnic | 1 |
| Mykola Khokhlov | National University Zaporizhzhia Polytechnic | 1 |
| Rostam Affendi Hamzah | Universiti Teknikal Malaysia Melaka | 1 |
| Mithilanandini S. Magenthiran | Universiti Teknikal Malaysia Melaka | 1 |
| Izadora Binti Mustaffa | Universiti Teknikal Malaysia Melaka | 1 |
| Safarudin Gazali Herawan | Binus University | 1 |
| Jamil Alsayaydeh | Affiliation unknown | 1 |
| Solomiia Liaskovska | Affiliation unknown | 1 |
| Yevhen Martyn | Affiliation unknown | 1 |
| Volodymyr Baidych | Khmelnytskyi National University | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.