Traffic Sign Recognition Using Computer Vision

Keywords:
Traffic Signs, Computer Vision, Machine Learning, Traffic Safety

Abstract:
This paper presents a comprehensive study on the development of a traffic sign recognition system based on computer vision, which is crucial for improving road safety and supporting intelligent transport systems (ITS). By using advanced image processing techniques and machine learning algorithms, this research aims to create a reliable system capable of accurately recognizing and classifying various traffic signs. The methodology includes collecting a diverse set of traffic sign images, applying image enhancement techniques, and utilizing deep learning models for precise recognition in different environmental conditions. Experimental results indicate the system’s high accuracy in recognizing traffic signs, even in cases with complex backgrounds, demonstrating its potential for integration into autonomous vehicles and advanced driver assistance systems (ADAS). This research contributes to efforts aimed at enhancing road safety and improving traffic management through automated traffic sign recognition.

CITATION:

IEEE format

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V. Radojčić, M. Dobrojević, “Traffic Sign Recognition Using Computer Vision,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2025, pp. 10-15. doi:10.15308/Sinteza-2025-10-15

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Radojčić, V., Dobrojević, M. (2025). Traffic Sign Recognition Using Computer Vision. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2025-10-15

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