Sunday, November 21, 2010

Biometric Recognition Methodology part 2/4 - Feature Extraction

3.3 Feature Extraction

Previously each face image, $\Gamma_i$ of size   is converted into a big matrix where each row, M presented the image and column is P = XY  and revenue difference matrix A with its size (M x P).  This section (Figure 3.5) described the eigenvalues and eigenvectors using Jacobi’s method, dimension reductions, eigenfaces transformations, features vectors representations and how the eigenfaces is used to rebuild the face images.

 Figure 3.5: Diagram for Eigenfaces Formations