State model based face mask detection

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    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.

     

     


  • Keywords


    ATM; Masked face Images; Surveillance; Viola-Jones Algorithm.

  • References


      [1] Sambarta Ray, Souvik Das, Dr. Anindya Sen,“An Intelligent Vision System for monitoring Security and Surveillance of ATM”, IEEE INDICON 2015

      [2] Y. Xia, and F. Coenen, “Face Occlusion Detection Based on Multitask Convolution Neural Network,” in Proceedings of 12th International Conference on IEEE Fuzzy Systems and Knowledge Discovery (FSKD), pp.375-379, 2015.

      [3] A. Maghraby M. Abdalla O. Enany, M.Y.El Nahas “Detect and Analyze Face Parts Information using Viola- Jones and Geometric Approaches” International Journal of Computer Applications (0975 – 8887) Volume 101– No.3, September 2014.

      [4] Zhang Jian, Song Wan-Juan, "Face detection for security surveillance system," Computer Science and Education (ICCSE), 2010 5th International Conference on, 2010, On page(s): 1735-1738.

      [5] C. Wen, S. Chiu, Y. Tseng, and C. Lu, “The Mask detection technology for occluded Face analysis in the surveillance system,” Journal of Forensic Science, vol. 50, no. 3, pp. 1-9,May 2005.

      [6] G. Kim, J. K. Suhr, H. G. Jung, and J. Kim, “Face occlusion detection by using b-spline active contour and skin color information,” In Proceedings of the International Conference on Control, Automation, Robotics and Vision, Dec. 2010, pp. 627-632.


 

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Article ID: 11805
 
DOI: 10.14419/ijet.v7i2.22.11805




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