Face Biometrics Based on Principal Component Analysis and Linear Discriminant Analysis

  title={Face Biometrics Based on Principal Component Analysis and Linear Discriminant Analysis},
  author={Lih-Heng Chan and Sh-Hussain Salleh and Chee-Ming Ting},
Problem statement: In facial biometrics, face features are used as th e required human traits for automatic recognition. Feature extracted from f ace images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Anal ysis (PCA) and Linear Discriminant Analysis (LDA). First, PCA is used for dimension reduction, where original face images are projected into lower… CONTINUE READING
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