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) …

Face is a complex multidimensional visual model and developing a computational model for
face recognition is difficult. The paper presents a methodology for face recognition based on …

Principal Component Analysis (PCA) has been widely used for efficient representation of
face images data in a low dimensional subspace. In this study, we use PCA to analyse …

With the growth of information technology there is a greater need of high security, so
biometric authentication systems are gaining importance. Face recognition is more used …

After 9/11 tragedy, governments in all over the world started to look more seriously to the
levels of security they have at their airports and borders. Countries annual budgets were …

This paper proposes a face recognition scheme that enhances the correct face recognition
rate as compared to conventional Principal Component Analysis (PCA). The proposed …

A new approach to the face recognition problem is presented through combining Fourier
descriptors with principal component analysis (PCA) and neural networks. Here the faces …

This paper presents a pattern recognition framework for face recognition based on the
combination of Radon and discrete cosine transforms (DCT). The property of Radon …

Face authentication is a significant problem in pattern recognition. The face is not rigid it can
undergo a large variety of changes in illumination, facial expression and aging. Principal …