A Review on Secure Helmet Wearing Detection by using Image Processing and Machine Learning

Author(s):

Jadhav Aparna Subhash , S B Patil College Of Engg, Indapur; Gaikwad Pragati Rajesh, S B Patil College Of Engg, Indapur; Jadhav Komal Dnyandeo, S B Patil College Of Engg, IndapurS B Patil College Of Engg, IndapurS B Patil College Of Engg, Indapur; Prof. Ekatpure J. N., S B Patil College Of Engg, Indapur

Keywords:

ViBe, Histogram of oriented gradient, Support vector machine, Color feature recognition

Abstract:

Secure helmet wearing detection is very necessary in power substation. At first, the ViBe background modelling algorithm is exploited to detect moving object under a view of fix surveillant camera in power substation. After obtaining the movement region of interest, the Histogram of Oriented Gradient (HOG) feature is squeeze out to relate inner human. And then, based on the result of HOG quality selection, the Support Vector Machine (SVM) is developed to classify walkers. Finally, the safety helmet detection will be executed by colour feature identification. gripping experimental results indicated the accuracy and effectiveness of our proposed method .The U.S. construction industry suffers from the large amount of fatalities among all factories, that is, one of five workman expires in private factories were in power substation. Tremendous loss has occurred to the workers family members, the factory, and the countries. Considering the highest and increasing number of substation projects that are being handled in the U.S., there is a highest necessity of developing innovative methods to automatically monitor the safety for the workers at power substation.

Other Details:

Manuscript Id	:	IJSTEV4I5013
Published in	:	Volume : 4, Issue : 5
Publication Date	:	01/12/2017
Page(s)	:	45-46

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