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September 23, 2025Deleted Journal1 citationsOpen Access

A Computer Vision-Based Vehicle Speed Monitoring and Reporting System

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CDClement DanladiAMA. S. MohammedAUAbraham U. Usman

Key Points

  • The developed system achieves an overall accuracy of 96.62% in speed estimation, significantly tackling over-speeding.
  • A mean absolute error of 0.93 and a root mean square error of 1.40 highlight the high precision of the vehicle speed estimation.
  • Background subtraction methods were utilized for speed estimation, combined with a novel approach to license plate extraction.
  • This advancement in traffic management technology may improve road safety and contribute to efficient urban planning.

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.

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Danladi et al. (2025) studied this question.

synapsesocial.com/papers/68d473a631b076d99fa6be8fhttps://doi.org/10.62292/10.62292/njp.v34i3.2025.382
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