DETECTION OF NON-HELMET RIDERS AND EXTRACTION OF LICENSE PLATE NUMBER USINGYOLO V2 AND OCR METHOD

Abstract

In current situation, we come across various problems in traffic regulations in India which can be solved with different ideas. Riding motorcycle/mopeds without wearing helmet is a traffic violation which has resulted in increase in number of accidents and deathsin India. Existing system monitors the trafficviolations primarily through CCTVrecordings, where the traffic police have to look into the frame where the traffic violation is happening, zoom into the licenseplate in case rider is not wearing helmet. Butthis requires lot of manpower and time as the traffic violations frequently and the number of people using motorcycles isincreasing day-by-day. What if there is asystem, which would automatically look for traffic violation of not wearing helmet while riding motorcycle/moped and if so, would automatically extract the vehicles’ license plate number. Recent research have successfully done this work based on CNN, R-CNN, LBP, HoG, HaaR features,etc. But these works are limited with respect to efficiency, accuracy or the speed with which object detection and classification is done. In this research work, a Non-Helmet Rider detection system is built which attempts to satisfy the automation of detecting the traffic violation of not wearing helmet and extracting the vehicles’ license plate number. The main principle involved is Object Detection using Deep Learning at three levels. The objects detected are person, motorcycle/moped at first level using YOLOv2, helmet at second level using YOLOv3, License plate at the last level using YOLOv2. Then the license plateregistration number is extracted using OCR (Optical Character Recognition). All thesetechniques are subjected to predefined conditions and constraints, especially the license plate number extraction part. Since, this work takes video as its input, the speed of execution is crucial. We have used above said methodologies to build a holistic systemfor both helmet detection and license plate number extraction.