Author(s) :
T. V. Ananda Babu, B. Pavithra, K. Naveen, B. Pavan, C. Shanmukh, D. Chiranjeevi
Conference Name :
Sri Venkatesa Perumal College of Engineering and Technology
Abstract :
Road safety is of prime importance, as road accidents are among the biggest cause number of death in the country. Road accidents are primarily due to violators and lawbreakers of road safety rules like not wearing helmets, triple riding, etc. Even though there are many smart systems to monitor these violations, it is complicated to keep track of the data and view it efficiently from anywhere. Also, monitoring the permit details of other state vehicles is hard. A method was proposed to address this issue based on deep learning and optical character recognition (OCR). Here, we detect the riders not wearing helmets and triple riders using object detection by comparing YOLO versions. This simplifies the task of traffic police, who can’t continuously and efficiently monitor all the violators. A number of items can be recognized by the real time object recognition system YOLO in a single frame. It recognizes objects more precisely and faster than other recognition systems. It can predict up to 9,000 classes and even unseen classes. For number plate detection, we use OCR based character recognition. The recognized license plate images of violators are captured and stored in a database, which is then sent to the concerned department.
No. of Downloads :
3