Abstract

Currently, there are several issues with Indian traffic regulations that can be resolved with various proposals. Driving a motorcycle or moped without wearing a helmet is a traffic infraction that has increased the incidence of collisions and fatalities in India. The current method largely uses CCTV recordings to keep track of traffic offences. The traffic authorities must take into account the frame in which the infraction is occurring and zoom in on the licence plate in the event that the cyclist is not wearing headgear. However, due to frequent traffic violations and the growing number of bike users, this requires a significant amount of labour as well as time. In this research study project, a system is designed to detect non-helmeted riders in an effort to automate the detection of this traffic infraction as well as the extraction of the vehicle's licence plate number. The key idea is that Deep Learning at 3 degrees is used for Item Discovery. Person, motorcycle or scooter at first level using YOLOv2, helmet at second level using YOLOv3, and licence plate at third level using YOLOv2 is the objects recognised. After that, OCR is used to extract the licence plate registration number (Optical Character Recognition). In fact, we used more of the aforementioned methods to create a substitute system that can recognise helmets and remove licence plate numbers.

Description