International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | Apr 2025
p-ISSN: 2395-0072
www.irjet.net
VEHICLE SPEED MEASUREMENT USING STEREO CAMERA PAIR Harshal Bankar1, Aditya Jagtap2, Prajwal Injekar Gurav3, Prof. R.R. Dhaygude4 1,2,3 Department Of Computer Engineering, SVPM’s College Of Engineering, Malegaon BK, Maharashtra, 412115,
India. 4Prof., Department Of Computer Engineering, SVPM’S College Of Engineering Malegaon BK, Baramati,
Maharashtra, India. ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Vehicle speed estimation is an essential
3D depth information through synchronized camera setups, resulting in more precise speed estimations.
component of traffic monitoring, law enforcement, and autonomous driving. Traditional speed measurement techniques, such as radar and LIDAR, are accurate but often expensive and intrusive. This paper presents an efficient stereo vision-based approach for vehicle speed estimation using synchronized camera pairs. Our system utilizes license plate detection, feature tracking, triangulation, and optimized frame selection to improve computational efficiency while maintaining high accuracy. A key innovation of our method is frame reduction through clustering algorithms (DBSCAN), which significantly reduces computational overhead without compromising accuracy. By applying Kalman filtering for robust tracking and RANSAC-based outlier removal, we enhance precision in vehicle trajectory reconstruction. The system processes highframe-rate video (60 FPS) and estimates speed with a mean absolute error of below 1 km/h and a standard deviation of less than 0.5 km/h. The method was validated using realworld datasets recorded via stereo mobile cameras and ground-truth speedometer readings from vehicles. Experimental results show that our technique achieves 40% computational efficiency improvement while maintaining a high accuracy rate. The findings suggest that this approach is suitable for real-time traffic enforcement and intelligent transportation systems. Future work includes integrating deep learning for enhanced license plate detection, expanding datasets to diverse weather conditions, and deploying the system on edge computing platforms for real-time applications.
Despite their advantages, stereo camera-based systems require careful calibration, are affected by environmental conditions, and may encounter challenges such as occlusions in high-density traffic environments. Moreover, the efficiency and accuracy of these systems depend on the selection of appropriate feature extraction and tracking methodologies. This research focuses on refining frame processing techniques to strike a balance between computational efficiency and measurement precision in realtime applications. Stereo reconstruction methods generally fall into three categories: local, semi-global, and global approaches. Our approach adopts a local and sparse strategy, prioritizing selected trajectory points instead of full scene reconstruction, thereby reducing computational overhead while maintaining measurement accuracy. Key contributions of this paper include: License plate detection and tracking in stereo images for vehicle localization. Triangulation-based 3D position estimation along the vehicle's trajectory. A refined motion model for accurate speed computation. These components collectively contribute to an effective and reliable stereo vision-based speed measurement system that aligns with established metrological standards.
Key Words: Stereo Camera Systems, Traffic Monitoring, Triangulation Techniques, Feature Extraction, Tracking Algorithms, 3D Information, Frame Reduction, Accuracy Analysis.
1.INTRODUCTION Accurate vehicle speed measurement is essential in fields such as traffic regulation, accident prevention, autonomous vehicle guidance, and law enforcement. Conventional speed detection technologies, including radar and LIDAR, have been widely used; however, they often come with high implementation costs, susceptibility to interference, and limitations in complex traffic scenarios. In contrast, stereo camera systems have emerged as an efficient and nonintrusive alternative, capable of capturing
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Fig -1: Left and Right Stereo Image
2. LITERATURE SURVEY Several vision-based vehicle speed estimation techniques have been proposed in prior research. Traditional speed
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