• Y. SHARMISTA
• SK.SADDAM HUSSAIN
• A.SHRUTHI
• V.SRAVANI
• B.SAMPATH KUMAR

We now face a number of issues with India's traffic restrictions, many of which have workable solutions. Without a helmet, it is illegal to drive a motorbike or scooter in India, which has led to a rise in accidents and fatalities. The current system largely uses CCTV records to monitor traffic offences, requiring traffic police to zoom in on the licence plate in the event that the helmet is not worn by the passanger and look into the frame where the infringement is taking place. However, given the high frequency of traffic offences and the rising daily use of motorbikes, this demands a significant amount of labour and time. What if there was a system that would check for traffic violations like riding a motorbike or moped without a helmet and, if found, it would extract the number plate from the data automatically of the offending car. Recent studies have successfully completed this task using features. However, these efforts have limitations in terms of effectiveness, precision, or how quickly objects may be identified and categorised. A non-helmet rider identification system is created in this research study in an effort to automate the process of identifying the traffic infraction of not wearing a helmet and obtaining the licence plate number of the offending vehicle. Object Detection using Deep Learning at three layers is the key idea at play. People, motorcycles or mopeds were discovered at the first level using YOLOv2, helmets were detected at the second level using YOLOv3, and licence plates were detected at the final level using YOLOv2. After that, OCR is used to retrieve the licence plate registration number. All of these methods are subject to predetermined restrictions and circumstances, particularly the component that extracts licence plate numbers. The readings of the output are counted as we take the input in the form of video. We made software as a solution to detect helmet and number plate extraction.

ANPR, Machine Learning, Image Processing, OpenCV, Pytesseract, OCR.

"VEHICLE NUMBER PLATE DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 12, page no.d543-d549, December-2022, Available :http://www.jetir.org/papers/JETIR2212373.pdf

"VEHICLE NUMBER PLATE DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 12, page no. ppd543-d549, December-2022, Available at : http://www.jetir.org/papers/JETIR2212373.pdf