Face Recognition Using Principal Component Analysis in MATLAB

Authors

  • Prabhjot Singh Department of ECE, CGC-COE, Landran, Mohali, Punjab, India
  • Anjana Sharma Department of ECE, CGC-COE, Landran, Mohali, Punjab, India

Keywords:

Eigenface, Eigenvalues, Detection, PCA, Recognition

Abstract

The paper present an semi-automated program for human face recognition. A self prepared database of different faces is used. Task of removing background from the image is a challenge but on the other hand by implementing Viola-Jones face detection algorithm and by Principal Component analysis it is possible. An application of system can be real time implementation of face recognition system. A robust and reliable form of recognition can be done by using Principal Component analysis. In the process Eigen faces or Eigen values are selected by PCA calculating the nearest face or value and then displaying result. This biometric system has real time application as used in attendance systems.

 

References

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Published

2015-02-28

How to Cite

[1]
P. Singh and A. Sharma, “Face Recognition Using Principal Component Analysis in MATLAB”, Int. J. Sci. Res. Comp. Sci. Eng., vol. 3, no. 1, pp. 1–5, Feb. 2015.

Issue

Section

Research Article

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