Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 577-579.

• Interdiscipline & Application • Previous Articles     Next Articles

Design and Improvement of Face Recognition System Based on PCA

LI Meng-xiao1, YAO Shi-yuan1,2   

  1. Electric Engineering and Information Department,Sowthwest Petroleum University,Chengdu 610500,China1;
    Oil and Gas Automation Lab,Chengdu 610500,China2
  • Online:2019-06-14 Published:2019-07-02

Abstract: Principal Component Analysis (PCA) is a multivariate statistical analysis method whichuses feature vectors to analyze sample data and reduce the high-dimension of the feature vectors.In order to solve the problem of high image dimension and large amount of direct calculation when PCA method is used for face recognition,a new feature value decomposition method is adopted and the filter is used to remove the noise of the original image.The face recognition system was built on MATLAB platform,and the common PCA method and the PCA method with filtering pretreatment were compared and analyzed.The experiment proved that the system with filtering processing has certain advantages in performance andcertain reference value practical application.

Key words: Eigenvalue decomposition, Face recognition, Filtering, PCA

CLC Number: 

  • TP391.4
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