Open AccessState model based face mask detection
Author(s) -
Muthu Subash Kavitha,
Mohamed Mansoor Roomi S,
K. Manju Priya,
Bavithra Devi K
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.22.11805
Subject(s) - computer science , face detection , face (sociological concept) , artificial intelligence , computer vision , mixture model , torso , gaussian , gaussian network model , pattern recognition (psychology) , facial recognition system , medicine , social science , physics , quantum mechanics , sociology , anatomy
The Automatic Teller Machine plays an important role in the modern economic society. ATM centers are located in remote central which are at high risk due to the increasing crime rate and robbery.These ATM centers assist with surveillance techniques to provide protection. Even after installing the surveillance mechanism, the robbers fool the security system by hiding their face using mask/helmet. Henceforth, an automatic mask detection algorithm is required to, alert when the ATM is at risk. In this work, the Gaussian Mixture Model (GMM) is applied for foreground detection to extract the regions of interest (ROI) i.e. Human being. Face region is acquired from the foreground region through the torso partitioning and applying Viola-Jones algorithm in this search space. Parts of the face such as Eye pair, Nose, and Mouth are extracted and a state model is developed to detect mask.