Implementation of Facial Recognition for Home Security Systems

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    In this paper, the design and development of a home security system has been detailed which uses facial recognition to conform the identity of the visitor and taking various security measures when an unauthorized personnel tries accessing the door. It demonstrates the implementation of one of the most popular algorithm for face recognition i.e. principal component analysis for the purpose of security door access. Since PCA converts the images into a lower dimension without losing on the important features, a huge set of training data can be taken. If the face is recognized as known then the door will open otherwise it will be categorized as unknown and the microcontroller (Arduino Uno) will command the buzzer to start ringing.

     

     


  • Keywords


    Arduino Uno; Covariance, Eigenvalue; Eigenvector; Eigen face; Eigen vector; Euclidean distance; Manhattan distance; PCA

  • References


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      [3] M. Turk, A. Pentland: Face Recognition using Eigenfaces, Conference on Computer Vision and Pattern Recognition, 3 – 6 June 1991, Maui, HI , USA, pp. 586 – 591

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      [8] Principal component analysis Herve Abdi and Lynne J. Williams2J. H. Davis and J. R. Cogdell

      [9] ] K. I. Diamantaras and S. Y. Kung, “Principal Component Neural Networks: Theory and Applications”, John Wiley & Sons,Inc., 1996

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Article ID: 20706
 
DOI: 10.14419/ijet.v7i4.10.20706




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