Comparative study of face recognition techniques that use joint transform correlation and principal component analysis
Abdul Rahman Alsamman, Mohammad S. Alam · Applied Optics · 2005
Face recognition based on principal component analysis (PCA) that uses eigenfaces is popular in face recognition markets. We present a comparison between various optoelectronic face recognition techniques and a PCA-based technique for face recognition. Computer simulations are used to study the effectiveness of the PCA-based technique, especially for facial images with a high level of distortion. Results are then compared with various distortion-invariant optoelectronic face recognition algorithms such as synthetic discriminant functions (SDF), projection-slice SDF, optical-correlator-based neural networks, and pose-estimation-based correlation.