Real Time Braille & Sign Language Detection Using  Artificial Neural Networks

Mahin, Tanveer Mahmood; Zerin, Jannatul Ferdous Islam; Ava, Nafisa Tabassum

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dc.contributor.author	Mahin, Tanveer Mahmood
dc.contributor.author	Zerin, Jannatul Ferdous Islam
dc.contributor.author	Ava, Nafisa Tabassum
dc.date.accessioned	2025-02-27T06:01:34Z
dc.date.available	2025-02-27T06:01:34Z
dc.date.issued	2024-06-27
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[5] Sanzidul Islam, Sadia Sultana Sharmin Mousumi, AKM Shahariar Azad Rabby, Sayed Akhter Hossain, Sheikh Abujar, A Potent Model to Recognize Bangla Sign Language Digits Using Convolutional Neural Network, Procedia Computer Science, Volume 143, 2018, Pages 611-618, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2018.10.438. [6] Abdullah Al Jaid Jim, Ibrahim Rafi, Md. Zahid Akon, Uzzal Biswas, Abdullah-Al Nahid, KU-BdSL: An open dataset for Bengali sign language recognition, Data in Brief, Volume 51, 2023, 109797, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2023.109797. [7] F. Yasir, P. W. C. Prasad, A. Alsadoon, A. Elchouemi and S. Sreedharan, "Bangla Sign Language recognition using convolutional neural network," 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kerala, India, 2017, pp. 49-53, doi: 10.1109/ICICICT1.2017.8342533. [8] S. A. 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[14] Jie Li and Xiaoguang Yan, "Optical Braille character recognition with Support-Vector Machine classifier," 2010 International Conference on Computer Application and System Modeling (ICCASM 2010), Taiyuan, 2010, pp. V12-219-V12-222, doi: 10.1109/ICCASM.2010.5622245. [15] T. Li, X. Zeng and S. Xu, "A Deep Learning Method for Braille Recognition," 2014 International Conference on Computational Intelligence and Communication Networks, Bhopal, India, 2014, pp. 1092-1095, doi: 10.1109/CICN.2014.229. [16] Renqiang Li, Hong Liu, Xiangdong Wang, and Yueliang Qian. 2018. DSBI: Double Sided Braille Image Dataset and Algorithm Evaluation for Braille Dots Detection. In Proceedings of the 2018 2nd International Conference on Video and Image Processing (ICVIP '18). Association for Computing Machinery, New York, NY, USA, 65–69. https://doi.org/10.1145/3301506.3301532. 54 [17] T. Okamoto, T. Shimono, Y. Tsuboi, M. Izumi and Y. Takano, "Braille Block Recognition Using Convolutional Neural Network and Guide for Visually Impaired People," 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, Netherlands, 2020, pp. 487-492, doi: 10.1109/ISIE45063.2020.9152576. [18] Shokat S, Riaz R, Rizvi SS, Khan I, Paul A. Characterization of English Braille Patterns Using Automated Tools and RICA Based Feature Extraction Methods. Sensors. 2022; 22(5):1836. https://doi.org/10.3390/s22051836	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/2319
dc.description	Supervised by Prof. Dr. Golam Sarowar, Department of Electrical and Electronic Engineering (EEE) Islamic University of Technology (IUT) Board Bazar, Gazipur, Bangladesh This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2024	en_US
dc.description.abstract	This research focuses on developing a real-time Braille and sign language detection system using artificial neural networks to enhance accessibility for visually and verbally impaired individuals. We developed novel datasets that can capture the real world context & employed advanced deep learning models, including Convolutional Neural Networks (CNNs) and YOLO, and utilized comprehensive data preprocessing techniques to ensure robustness. Our methodology achieved significant improvements in detection accuracy, validated through extensive performance metrics. The developed prototypes were tested in real-world scenarios, demonstrating practical effectiveness. This research advances assistive technologies, providing a foundation for future innovations and improving the quality of life for the targeted individuals.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Electrical and Elecrtonics Engineering(EEE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.subject	Machine learning, image detection, YOLOv8, Object detection, OpenCV	en_US
dc.title	Real Time Braille & Sign Language Detection Using Artificial Neural Networks	en_US
dc.type	Thesis	en_US