Many people in the world, particularly in countries such as Thailand in South East Asia, use motorcycles as their primary mode of transport. Unfortunately many motorcycle riders do not wear helmets which are essential to protect them from severe injury in the case of an accident. This is particularly true for the youth of these countries, where numerous young people are severely injured and the potential for severe injury is high.
The plan was to apply the results of this research to closed traffic environments, such as universities, where the identification and control of individuals as part of an automated framework is an achievable goal.
Intelligent techniques in transportation systems are gaining in popularity due to the availability of applicable techniques and the lowering of the costs of the basic technologies such as video cameras and computers. Furthermore computer vision is a maturing field where applications such as this can be realized, particularly with the use of freely available open source tools such as the open computer vision (OpenCV) library. At the time, despite these continual developments, the number of publications regarding motorcycle helmet detection were few, providing ample opportunity for new research into this potentially highly useful field.