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), Linear Discriminant Analysis (LDA) and Line Edge Map (LEM). These algorithms show different rates of accuracy under different conditions. The automatic recognition of human faces presents a challenge to the pattern recognition community. Typically, human faces are different in shapes with minor similarity from person to person. Furthermore, lighting condition changes, facial expressions and pose variations further complicate the face recognition task as one of the difficult problems in pattern analysis.