Automatic Motorcyclist Helmet Rule Violation Detection using TensorFlow & Kera’s in OpenCV


  • Swagatam Mukhuty


Motorcycle, helmet, Computer Vision, TensorFlow, Kera’s, barrier.


Traffic accidents are now rapidly increasing in numerous countries over the years, due to motorcyclists' international disregard for traffic safety, which has resulted in accidents and fatalities. To combat this issue, most nations have regulations requiring two-wheeler motorcyclists to wear helmets, thus it is critical for bikers to realise the dangers of driving outside without. Motorcyclists who don't even wear a helmet are all at the biggest danger of catastrophic brain damage; whether they are injured in an incident without covering, the skull is vulnerable to a severe hit. In India, there is indeed a rule that requires riders to wear helmets, and not riders. Someone riding a motorbike without even a helmet risks being involved in a crash or suffering head trauma. Everybody, even kids, should indeed be recommended to carry a helmet. As a result, we designed a system with in computer vision that is founded on TensorFlow and Keras. Including in real time, the system can detect not just whether riders are wearing helmets. If some of them seem to be there without a helmet, the technology will closely evaluate the incident and issue a compliance report. The technology, which may be used in mall, workplaces, super markets, schools, and colleges, allows users to enter only once a helmet is detected by an automatic barrier. It will undoubtedly have an impact on the use of helmets which will save people's lives.




How to Cite

Swagatam Mukhuty. (2021). Automatic Motorcyclist Helmet Rule Violation Detection using TensorFlow & Kera’s in OpenCV. Journal of Research Proceedings, 1(2), 123–137. Retrieved from