A Computer Vision-Based Vehicle Speed Monitoring and Reporting System

Authors

Keywords:

Computer Vision, Vehicle Speed Estimation, License Plate Detection, Traffic Management, Over-Speeding Detection

Abstract

The detection and enforcement of over-speeding regulations remain a significant challenge due to limitations in existing vehicle speed estimation techniques. This study addresses this issue by developing a high-accuracy vehicle speed estimation system that incorporates a novel approach for license plate region extraction and over-speeding detection. The methodology employed involves the use of background subtraction methods to estimate vehicle speed, combined with a proprietary algorithm for vehicle plate region extraction. This information is then processed by a reporting system that identifies over-speeding vehicles. Results from extensive testing reveal a mean absolute error of 0.93 and a root mean square error of 1.40 in speed estimation, demonstrating high accuracy and precision of the developed system. Additionally, the mean absolute percentage error of 3.38% further substantiates the effectiveness of the system, leading to an overall accuracy of 96.62% in speed estimation. This advancement in traffic management technology has the potential to improve road safety, reduce traffic violations, and contribute to more efficient and streamlined urban planning.

Author Biographies

Clement Danladi

School of Electrical Engineering and Technology, Federal University of Technology, Minna, Nigeria.

Abubakar Sadiq Mohammed

School of Electrical Engineering and Technology, Federal University of Technology, Minna, Nigeria.

Abraham Usman

School of Electrical Engineering and Technology, Federal University of Technology, Minna.

Dimensions

Chiranjeevi, K., Venkateswarlu, K., and Babu, E. C. (2023). Vehicle Monitoring and Speed Recognition System. International Journal of Creative Research Thoughts (IJCRT), 11(6), 886-890. IJRTI

Fernandez Llorca, D., Hernandez Martinez, A., & Garcia Daza, I. (2021). Vision‐based vehicle speed estimation: A survey. IET Intelligent Transport Systems, 15(8), 987-1005. https://doi.org/10.1049/itr2.12079

Kakde, A., Sangode, L., Singh, S. K., and Ladekar, Y. (2023). Vehicle Speed Detection. International Journal of Advanced Research in Computer and Communication Engineering, 12(5), 1111-1116. DOI: 10.17148/IJARCCE.2023.125189

Khan, M. M. and Srinivas, K. (2020). Vehicle Speed Detection using Python. International Research Journal of Engineering and Technology (IRJET), 7(5), 218-222. https://irjet.net/archives/V7/i5/IRJET-V7I546.pdf

Khorasani, M. (2020). Image Processing Based Vehicle Number Plate Detection and Speeding Radar. Medium. Retrieved online at https://pub.towardsai.net/image-processing-based-vehicle-number-plate-detection-and-speeding-radar-aa375952d0f6

Khosravi, H., Asgarian Dehkordi, R., & Ahmadyfard, A. (2022). Vehicle speed and dimensions estimation using on-road cameras by identifying popular vehicles. Scientia Iranica, 29(5), 2515-2525.

Lahari, S. V. S., Subha, G. S. S. K., Raju, V. B. M., and Vishnu, M. S. (2023). Vehicle Over Speed Detection using Centroid Tracking Technique. Journal of Emerging Technologies and Innovative Research, 10(4), 524-530.

Mahalakshmi, P. D., & Babu, D. M. (2019). Vehicle Speed Estimation using Haar Classifier Algorithm. International Journal of Trend in Scientific Research and Development (IJTSRD), 4(1), 243-246. 51 Vehicle Speed Estimation using Haar Classifier Algorithm

Mittal, A., Bansal, P., and Khushwah, A. (2021). Vehicle Detection and Tracking of Speed using Computer Vision. International Journal of Innovative Research in Technology, 8(2), 723-727. IJIRT152236_PAPER.pdf

Rajora, S., Chhonkar, R., Sharma, S., and Bhatia, S. (2022). Vehicle Feature Detection using Image Processing and OpenCV. International Journal of Research Publication and Reviews, 3(5), 482-485. Vehicle Feature Detection Using Image Processing and OPENCV

Tourani, A., Shahbahrami, A., Akoushideh, A., Khazaee, S., & Suen, C. Y. (2019). Motion-based vehicle speed measurement for intelligent transportation systems. International Journal of Image, Graphics and Signal Processing, 10(4), 42. https://doi.org/10.5815/ijigsp.2019.04.04

Wiley, V., & Lucas, T. (2018). Computer vision and image processing: a paper review. International Journal of Artificial Intelligence Research, 2(1), 29-36. DOI: 10.29099/ijair.v2i1.42

Yang, Z., & Pun-Cheng, L. S. (2018). Vehicle detection in intelligent transportation systems and its applications under varying environments: A review. Image and Vision Computing, 69, 143-154. https://doi.org/10.1016/j.imavis.2017.09.008

Zhao, L., Tang, Y., & Wang, L. (2023). Research on vehicle speed identification method based on time interpolation method and feature point recognition. International Journal of Advanced Robotic Systems, 20(1), 17298806231153726. https://doi.org/10.1177/17298806231153726

Published

2025-09-22

How to Cite

Danladi, C., Mohammed, A. S., & Usman, A. (2025). A Computer Vision-Based Vehicle Speed Monitoring and Reporting System. Nigerian Journal of Physics, 34(3), 53-64. https://doi.org/10.62292/10.62292/njp.v34i3.2025.382

Issue

Vol. 34 No. 3 (2025): Nigerian Journal of Physics - Vol. 34 No. 3

Section

Articles
Copyright & Licensing

How to Cite

Danladi, C., Mohammed, A. S., & Usman, A. (2025). A Computer Vision-Based Vehicle Speed Monitoring and Reporting System. Nigerian Journal of Physics, 34(3), 53-64. https://doi.org/10.62292/10.62292/njp.v34i3.2025.382