Detection of bike rider without wearing helmet, and extract the number plate and store it into cloud database and send SMS to respective rule violators.
What it does
Using the existing video feeds from the cameras positioned on highways, traffic signal & busy roads, conduct the following: Detection of bike rider with / without wearing helmet Extraction of vehicle license plate Generation of receipt of bike rider without wearing helmet Send SMS to registered mobile number
Now-a-days two wheelers are the most preferred mode of transport. It is highly desirable for bike riders to use a helmet, but wearing helmets is often neglected by riders worldwide leading to accidents and deaths. To address this issue, most countries have laws which mandate the use of helmets for two-wheeler riders. In addition to the law, there is a significant proportion of the police force that discourages this behavior by issuing a traffic violation ticket. As of now, this process is manual and tedious. The proposed system is to solve this problem by automating the process of detecting the riders who are riding without helmets. Furthermore, the system also extracts the license plate, in extraction of license plate algorithm has five parts: image procurement, preliminary processing, fringe detection and segmentation, feature extraction and recognition of character number plates using suitable machine learning algorithms so that it could be used to issue traffic violation tickets. The system implements machine learning and image processing techniques to detect riders, riding two-wheelers, who are not wearing helmets. The system takes a video of traffic on public roads as the input and detects moving objects in the scene. A machine learning classifier is applied to the moving object to identify if the moving object is a two-wheeler. The license plate is provided as the output in case the rider is not wearing a helmet.