Face recognition (FR) is a challenging issue due to variation in expression, pose,
illumination and aging etc. In this paper hybrid combination of principal component analysis …

Face recognition system should be able to automatically detect a face in images. This
involves extraction of its features and then recognizes it, regardless of lighting, ageing …

In principal component analysis (PCA) algorithm for face recognition, the eigenvectors
associated with the large eigenvalues are empirically regarded as representing the changes …

Face recognition is one of the finest method or field to use for better accuracy and also
security. Face is comprising of multidimensional structure with complexity and for that …

Abstract Principal Component Analysis (PCA) turns out to be one of the most successful
techniques in face recognition systems as a statistical method for dimensionality reduction …

Human face recognition has been employed in different commercial and law enforcement
applications. It has also been employed for mug shots matching, bank-store security, crowd …

In this paper, we propose a PCA-based face recognition system implemented using the
concept of neural networks. This system has three stages, viz. pre processing, PCA and face …

Face recognition is a dynamic topic in the fields of biometrics. Many achievements have
been obtained in face recognition. Principal Components Analysis (PCA) and kernel …

Face recognition has been largely used in biometric field as a security measure at air ports,
passport verification, criminals' list verification, visa processing, and so on. Various literature …

A study of both face recognition and detection techniques is carried out using the algorithms
like Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA) …