• Miss. Dhanashri M. Divase
• Miss. Sonam K. Thorat
• Miss. Reshma D.Unde
• Prof. Rahul R. Rathod

Safety helmet wearing detection is very essential while traveling. We proposed a innovative and practical safety helmet wearing detection method based on image processing and machine learning. At first, the extract background modeling algorithm is exploited to detect motion object under a view of fix surveillant camera in power substation. After obtaining the motion region of interest, the Histogram of Oriented Gradient (HOG) feature is extracted to describe inner human. And then, based on the result of HOG feature extraction, the Support Vector Machine (SVM) is trained to classify pedestrians. Finally, the safety helmet detection will be implemented by color feature recognition. To ensure the safe operation of power equipments, more and more intelligent surveillance systems had been developed based on computer vision or image processing.

vibe; histogram of oriented gradient; support vector machine; color feature recognition.

"Real-time Safety Helmet Wearing Detection Based Using Face Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.675-678, May-2019, Available :http://www.jetir.org/papers/JETIR1905Q97.pdf

"Real-time Safety Helmet Wearing Detection Based Using Face Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp675-678, May-2019, Available at : http://www.jetir.org/papers/JETIR1905Q97.pdf