
International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 7 Issue 3
May-June 2025
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Improving Driver Safety through Automated Traffic Sign Recognition Systems
Author(s) | Ms. Saloni Gupta, Ms. Shubhi Gupta, Prof. Dr. Maria Jamal |
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Country | India |
Abstract | This research presents a CNN-based automated traffic sign recognition system designed to enhance driver safety by accurately detecting and classifying road signs in real time. The proposed TS-CNN model is trained on the GTSRB dataset, incorporating techniques like HSV segmentation, shape-based feature extraction, and data augmentation to improve robustness under various conditions. With a classification accuracy of 95% and fast inference speed, the system aids in reducing accidents caused by missed or misunderstood traffic signs, making it suitable for real-world driver assistance applications. |
Keywords | Traffic Sign Recognition, Convolutional Neural Network (CNN), Intelligent Transportation Systems, Driver Assistance, Real-Time Classification, Deep Learning, GTSRB Dataset, Image Processing, Road Safety, Feature Extraction |
Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
Published In | Volume 7, Issue 3, May-June 2025 |
Published On | 2025-05-04 |
DOI | https://doi.org/10.36948/ijfmr.2025.v07i03.43612 |
Short DOI | https://doi.org/g9hsd6 |
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E-ISSN 2582-2160

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IJFMR DOI prefix is
10.36948/ijfmr
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