Abstract
It is very important to protect the safety of the human head with helmet. Traditional detection for helmet wearing mainly relies on manual approach, which was more subjective that a missing condition may happen caused by fatigue and other factors. Owing to this situation, this paper proposed a method for automatic detection of operator without helmet in real-time. Firstly, Gaussian model for background subtraction is used to detect moving target. Secondly, HOG feature extraction can be used to classify the human target from vehicle. Then, a color feature extraction algorithm is proposed for helmet recognition. The algorithm has been applied into the real time monitoring system and verified with higher accuracy.
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