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Recognition of Face with Cross-Correlation Method and Principal Component Analysis


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1 Department of Computer Science & Engineering, Manav Bharti University, Solan, H.P., India
     

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Automated face recognition has become a major field of interest. Face recognition algorithms are used in a wide range of applications viz., security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different face recognition techniques by considering different test samples. The experimentation involved the use of Eigen faces and PCA (Principal Component Analysis). Another method based on Cross-Correlation in spectral domain has also been implemented and tested. Recognition rate of 90% was achieved for the above mentioned face recognition techniques.
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  • Recognition of Face with Cross-Correlation Method and Principal Component Analysis

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Authors

Anjaly
Department of Computer Science & Engineering, Manav Bharti University, Solan, H.P., India
Nisha Dua
Department of Computer Science & Engineering, Manav Bharti University, Solan, H.P., India

Abstract


Automated face recognition has become a major field of interest. Face recognition algorithms are used in a wide range of applications viz., security control, crime investigation, and entrance control in buildings, access control at automatic teller machines, passport verification, identifying the faces in a given databases. This paper discusses different face recognition techniques by considering different test samples. The experimentation involved the use of Eigen faces and PCA (Principal Component Analysis). Another method based on Cross-Correlation in spectral domain has also been implemented and tested. Recognition rate of 90% was achieved for the above mentioned face recognition techniques.