A Review on India Traffic Sign Detection Techniques

Kaushal Pravinbhai Patel; Dr. Sheshang Degadwala

doi:10.32628/CSEIT24103125

Authors

Kaushal Pravinbhai Patel Reserach Scholar, Department of Computer Engineering, Sigma University, Vadodara, Gujarat, India Author
Dr. Sheshang Degadwala Professor / HOD, Department of Computer Engineering, Sigma University, Vadodara, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT24103125

Keywords:

Traffic Sign Detection, Techniques, Review, Advancements

Abstract

This abstract delves into the realm of traffic sign detection techniques tailored for India's diverse and dynamic traffic environment. It navigates through traditional methods like color segmentation and template matching, juxtaposing them with the contemporary prowess of deep learning, particularly convolutional neural networks (CNNs). The intricacies of Indian roads, encompassing varied signage designs, fluctuating lighting conditions, and complex infrastructural nuances, are scrutinized in the context of these detection mechanisms. The narrative extends to discuss the amalgamation of IoT devices, real-time processing frameworks, and vehicle-mounted cameras to forge more efficient detection systems. Furthermore, the review underscores the transformative impact of machine learning advancements, spotlighting transfer learning and ensemble techniques as instrumental in augmenting detection accuracy and scalability. This abstract encapsulates a comprehensive exploration of India's traffic sign detection landscape, offering insights into ongoing trends, persistent challenges, and promising avenues for future research and development.

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D. D. Pandya, N. S. Gupta, A. Jadeja, R. D. Patel, S. Degadwala, and D. Vyas, “Bias Protected Attributes Data Balancing using Map Reduce,” in 6th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2022 - Proceedings, 2022, pp. 1540–1544. doi: 10.1109/ICECA55336.2022.10009363. DOI: https://doi.org/10.1109/ICECA55336.2022.10009363

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A. Patel, S. Degadwala, and D. Vyas, “Lung Respiratory Audio Prediction using Transfer Learning Models,” in 6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022 - Proceedings, 2022, pp. 1107–1114. doi: 10.1109/I-SMAC55078.2022.9986498. DOI: https://doi.org/10.1109/I-SMAC55078.2022.9986498

M. Shah, S. Degadwala, and D. Vyas, “Diet Recommendation System based on Different Machine Learners: A Review,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 290–295. doi: 10.1109/ICAIS53314.2022.9742919. DOI: https://doi.org/10.1109/ICAIS53314.2022.9742919

H. Gupta, D. Patel, A. Makade, K. Gupta, O. P. Vyas, and A. Puliafito, “Risk Prediction in the Life Insurance Industry Using Federated Learning Approach,” in MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings, 2022, pp. 948–953. doi: 10.1109/MELECON53508.2022.9842869. DOI: https://doi.org/10.1109/MELECON53508.2022.9842869

D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Ensemble Learning based Enzyme Family Classification using n-gram Feature,” in Proceedings - 2022 6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022, 2022, pp. 1386–1392. doi: 10.1109/ICICCS53718.2022.9788292. DOI: https://doi.org/10.1109/ICICCS53718.2022.9788292

B. Trivedi, S. Degadwala, and D. Vyas, “Parallel Data Stream Anonymization Methods: A Review,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 887–891. doi: 10.1109/ICAIS53314.2022.9743084. DOI: https://doi.org/10.1109/ICAIS53314.2022.9743084

P. Bam, S. Degadwala, R. Upadhyay, and D. Vyas, “Spoken Language Recognization Based on Features and Classification Methods: A Review,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 868–873. doi: 10.1109/ICAIS53314.2022.9743090. DOI: https://doi.org/10.1109/ICAIS53314.2022.9743090

R. Baria, S. Degadwala, R. Upadhyay, and D. Vyas, “Theoretical Evaluation of Machine And Deep Learning For Detecting Fake News,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 325–329. doi: 10.1109/ICAIS53314.2022.9742864. DOI: https://doi.org/10.1109/ICAIS53314.2022.9742864

S. Degadwala, D. Vyas, U. Chakraborty, A. R. Dider, and H. Biswas, “Yolo-v4 Deep Learning Model for Medical Face Mask Detection,” in Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021, 2021, pp. 209–213. doi: 10.1109/ICAIS50930.2021.9395857. DOI: https://doi.org/10.1109/ICAIS50930.2021.9395857

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S. Degadwala, D. Vyas, M. R. Hossain, A. R. DIder, M. N. Ali, and P. Kuri, “Location-Based Modelling and Analysis of Threats by Using Text Mining,” Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, pp. 1940–1944, 2021, doi: 10.1109/ICESC51422.2021.9532825. DOI: https://doi.org/10.1109/ICESC51422.2021.9532825