Intelligent Traffic Surveillance for Real-Time Vehicle Detection, License Plate Recognition, and Speed Estimation

• URL: http://arxiv.org/abs/2601.00344v1
• Date: Thu, 01 Jan 2026 13:54:29 GMT
• Title: Intelligent Traffic Surveillance for Real-Time Vehicle Detection, License Plate Recognition, and Speed Estimation
• Authors: Bruce Mugizi, Sudi Murindanyi, Olivia Nakacwa, Andrew Katumba,
• Abstract summary: This study proposes a real-time intelligent traffic surveillance system tailored to developing countries.<n>License plate detection using YOLOv8 achieved a mean average precision (mAP) of 97.9%.<n>Speed estimation used source and target regions of interest, yielding a good performance of 10 km/h margin of error.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Speeding is a major contributor to road fatalities, particularly in developing countries such as Uganda, where road safety infrastructure is limited. This study proposes a real-time intelligent traffic surveillance system tailored to such regions, using computer vision techniques to address vehicle detection, license plate recognition, and speed estimation. The study collected a rich dataset using a speed gun, a Canon Camera, and a mobile phone to train the models. License plate detection using YOLOv8 achieved a mean average precision (mAP) of 97.9%. For character recognition of the detected license plate, the CNN model got a character error rate (CER) of 3.85%, while the transformer model significantly reduced the CER to 1.79%. Speed estimation used source and target regions of interest, yielding a good performance of 10 km/h margin of error. Additionally, a database was established to correlate user information with vehicle detection data, enabling automated ticket issuance via SMS via Africa's Talking API. This system addresses critical traffic management needs in resource-constrained environments and shows potential to reduce road accidents through automated traffic enforcement in developing countries where such interventions are urgently needed.

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