A Novel Method of Traffic Rule Compliance Detection Using Morphological Operations at Toll Booths

International Journal of Electrical and Electronics Engineering

© 2023 by SSRG - IJEEE Journal

Volume 10 Issue 1

Year of Publication : 2023

Authors : Jayamala Kumar Patil, Priyadarshani Shivkumar Mali, Aarti Hemant Tirmare, Vinay Sampatrao Mandlik

10.14445/23488379/IJEEE-V10I1P114

How to Cite?

Jayamala Kumar Patil, Priyadarshani Shivkumar Mali, Aarti Hemant Tirmare, Vinay Sampatrao Mandlik, "A Novel Method of Traffic Rule Compliance Detection Using Morphological Operations at Toll Booths," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 1, pp. 148-159, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I1P114

Abstract:

Vehicle collisions cause fatalities and disability for individuals all over the world (s). In India, vehicle accidents caused by infractions of traffic laws claim more lives than naxal violence or natural calamities. However, people may drive while disregarding traffic laws, and doing so risks their lives. The main causes of traffic accidents are often careless lane switching and the usage of mobile devices. Additionally, these fatal traffic accidents' financial burden on the affected individuals and the government is significant. The government is investing a lot of money to spread awareness, motivate people to obey traffic laws, and organise many awareness campaigns to inform people to obey the law and save lives. Traffic cops now manually discover violations of traffic laws. The activity is time-consuming and chaotic, and there is a chance that the traffic police would operate dishonestly, which might result in more traffic rule violations. There has been a great deal of investigation into traffic management systems over the last 20 years but at the expense of infrastructure requirements. Sensorbased approaches have been utilised to monitor these breaches. This research describes how machine vision-based feature extraction utilising classification and matching algorithms on Raspberry Pi hardware may be used to identify violations of traffic rules on roads and highways. An inexpensive Raspberry Pi-based system based on feature extraction for monitoring and detecting infractions of traffic lanes and other rules. SIFT, SURF, ORB, KAZE, AKAZE, BRISK, and ROOTSIFT were also used to discover rule violations.

Keywords:

Feature extraction, Raspberry Pi, Road accidents, Sensor, Traffic and Highway.

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