Detection of Bike Riders without Helmet and Triple Riding using YOLO v3 model

As the number of bikes have been increasing throughout the years in several countries. he danger of demise has also increased 2.5 times among the riders without using a helmet contrasted with person wearing a helmet. To address this issue, most countries have laws which mandate the use of helmets for two-wheeler riders. This paper plans to unwind this issue by automating the technique for distinguishing the riders with and without helmets. The system takes a video of traffic on an open street as an information and recognizes the moving items inside the scene. This work proposes a system based on the location of individual or different riders taking a trip on bikes with no helmets. Inside the proposed approach, from the beginning stage, bike riders are recognized with the use of YOLOv3 model which is a consistent type of YOLO model, the forefront methodology for object distinguishing helps as such in distinguishing the riders with and without helmet. The vertical projection of binary image is used for counting the number of riders if it exceeds two.