Abstract: Vehicle Speed Detection and Estimation is an essential task for many traffic management and safety systems. In this research, we offer a novel computer vision-based method for real-time vehicle speed estimate and detection. To identify the cars and determine their speeds, our system first analyses video footage of the moving vehicles using image processing algorithms. On a dataset of actual traffic scenarios, we test the suggested algorithm, and the results show that it performs rather well in terms of accuracy. Potential uses for the suggested approach include traffic control, law enforcement, and intelligent transportation systems. Overall, this research helps to create methods for detecting and estimating vehicle speed that are accurate and efficient, which may greatly enhance traffic management and safety. The issue description, suggested solution, study methods, and findings are all briefly summarized in this abstract. It emphasizes the contribution to the area and draws attention to the research's importance and prospective uses. The abstract is succinct and informative, giving the reader enough details to comprehend the study and its significance to the subject.

Keywords: Image processing, computer vision, Nodejs, OpenCV, Image Processing, Moving Object Detection.

PDF | DOI: 10.17148/IJARCCE.2023.125189

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