A Review on India Traffic Sign Detection Techniques

Kaushal Pravinbhai Patel and Sheshang Degadwala

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 3, 436-449

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.

Keywords: Traffic Sign Detection; Techniques; Review; Advancements (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24103125
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i3:id:221

DOI: 10.32628/CSEIT24103125

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