BibTeX:

@article{IJIRSTV4I11043,
     title={Real Time Automatic Helmet Detection of Bike Riders},
     author={Kavyashree Devadiga, Yash Gujarathi, Pratik Khanapurkar, Shreya Joshi and Shubhankar Deshpande},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={4},
     number={11},
     pages={146--148},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV4I11043.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Nowadays two-wheeler is the most popular modes of transport. However, because of less protection there is a high risk involved. As a solution to this, it is highly desirable for bike-riders to use helmet. Observing the usefulness of helmet, Governments have made it punishable offense to ride a bike without helmet and have adopted manual strategies to catch the violators which has limitations of speed. Using video surveillance of the street, the proposed approach detects if the bike rider is wearing a helmet automatically without manual help. If a bike rider is detected not wearing a helmet, the number plate of the vehicle read and noted. A database will be generated with records to identify every offender accurately. The system implements pure machine learning in order to identify every type of helmet that it comes across with minimum computation cost.

Helmet detection system, Feature evaluation and selection, Vehicle classification, Machine Learning, optical character recognition