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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62411
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science and Technology
Nehru College of Engineering and Research Centre
Department of Computer Science and Technology
Nehru College of Engineering and Research Centre
Department of Computer Science and Technology
Nehru College of Engineering and Research Centre
Department of Computer Science and Technology
Nehru College of Engineering and Research Centre
Department of Computer Science and Technology
Nehru College of Engineering and Research Centre
Access to information is still a big challenge for visually impaired people. They often have to rely on others for tasks. This paper suggests an affordable assistive system using the Raspberry Pi 4. It helps people read on their own using Optical Character Recognition (OCR) and Text-to-Speech conversion in time. The system uses a 720p Raspberry Pi Camera to take pictures of printed text. These images are then processed using OpenCV to remove noise convert to grayscale and make the text clearer. This helps the system recognize characters accurately. The Tesseract OCR engine is used to extract text with precision. There is also a translation module that converts text regional language(Malayalam). The final output is converted into sounding speech using the Google Text-to-Speech (gTTS) library. The speech is then played through earphones. Experimental results show that the system can recognize text with 95% accuracy. It takes between 3.5 to 5.5 seconds to process the text. The system provides a scalable and inclusive 2solution. It helps impaired individuals by making it easier for them to access information in a multilingual environment. The Raspberry Pi 4 and OCR are key to this system. The system uses the Raspberry Pi 4 to make reading easier, for impaired people. It helps them read printed text on their own. The OCR and TTS conversion are parts of this system. They help the impaired individuals read and understand the text.
KEYWORDS
This paper introduced VoiceLens, a cost-effective, portable smart vision aid aimed at improving accessibility for visually impaired individuals via real-time text recognition and speech output. The system successfully showed that it could take pictures of printed text, process them, and turn them into understandable audio feedback by combining the Raspberry Pi platform with a camera module, Tesseract OCR, a translation layer, and the Google Text-to-Speech (gTTS) engine. Tests showed that the system worked well in different environments, with high recognition accuracy in good lighting and acceptable performance in more difficult situations. The system's ability to process data in real time, support multiple languages, and produce clear speech synthesis shows how useful it is as an assistive technology that encourages independence and inclusion. Future enhancements may concentrate on augmenting OCR resilience in low-light environments, refining recognition for intricate fonts, optimizing processing latency, and broadening language adaptability. In general, the proposed solution is a significant step toward creating assistive systems that are easy to use, cheap, and focused on the needs of visually impaired users.
1. M. Murali, S. Sharma, and N. Nagansure, “Reader and Object Detector for Blind,” 2020 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2020. 2. K. S. P., A. A., G. K., and H. S., “Raspberry Pi-Based Smart Assistance for Visually Impaired People,” 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2022. 3. A. Jojie, A. George, D. Dhanalal, and N. J., “Book Reader for Blind,” IOSR Journal of Engineering (IOSRJEN), 2018. 4. K. I. Khaleel and K. N. F. B. Ku Azir, “An Enhancement of Text-to-Speech (TTS) System Using Raspberry Pi,” Turkish Journal of Computer and Mathematics Education, vol. 12, no. 13, 2021. 5. S. Subash, P. N. Srivasta, S. Siddhesh, U. Ullas, and S. B. Santhosh, “Artificial Intelligence-Based Voice Assistant,” Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 2020. 6. M. Prabha, P. Saraswathi, J. Hailly, C. Sindhuja, and P. Udhaya, “Smart Glasses: A Visual Assistant for Visually Impaired,” 2023 11th International Conference on Emerging Trends in Engineering Technology – Signal and Information Processing (ICETET-SIP), Nagpur, India, 2023. 7. N. B. R., Y. Raju N. R., and A. S. Velidi, “Low-Cost Smart Glasses for People with Visual Impairments,” 2023 International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS), Bangalore, India, 2023. 8. M. Yaswanth, M. Madhavi, T. D. Kiran, and P. A. Vardhan, “Guide Me Glasses,” 2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication Engineering (ICATIECE), Bangalore, India, 2022. 9. A. Huynh, Z. Marchant, I. Singh, and F. Aveta, “Assistive Reading Device for Blind Individuals,” 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, USA, 2023. 10. F. T. Josh, J. J. Joseph, S. N. Morapakula, M. R., and P. A. Michael, “Handy Reader – A Shopping Guide to Visionless Using Raspberry Pi,” 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli,India,2022.
Publication Date
5/3/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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