Eigen faces are the set of Eigen vectors that when represented in computer vision can be used for face recognition. It is one of the oldest and most basic forms of facial recognition developed by Sirovich and Kirby in 1987 and used by Mathew A Turk and Alex P Pentland. This is a five-step process that leads to image recognition from the set of face images stored in the database. The steps are: The system must be initialized by entering the initial set of face images which are to be stored in a database. All images are processed and a covariance matrix is ​​obtained and the Eigen values ​​and their Eigen vectors are calculated for the matrix. Principal component analysis is used to select the Eigen vectors with the highest Eigen values. The image of the face to be recognized is processed to obtain its Eigen components and the weight of the image is calculated. The difference between the weight obtained and the weight of the individual images recognizes the face.2.1) INITIALIZATION OF THE IMAGES Each image can be represented by a vector in which each value of the vector represents a pixel of the image...