Eigenfaces are the set of eigenvectors when represented in computer vision and can be used for face recognition. It is one of the oldest and most fundamental forms of facial recognition developed by Sirovich and Kirby in 1987 and used by Mathew A Turk and Alex P Pentland. It is a five-step process that results in image recognition from the set of face images stored in the database. The steps are as follows: The system must be initialized by introducing the initial set of face images which must be stored in a database. All the images are processed and a covariance matrix is ​​obtained and the eigenvalues ​​and respective eigenvectors are calculated for the matrix.Principal component analysis is used to select the eigenvectors with the highest eigenvalues.The face image to be recognized is processed to obtain its eigencomponents and the weight of the image is calculated. The difference between the obtained weight and the weight of the individual images recognizes the face.2.1) INITIALIZATION OF IMAGES Each image can be represented by a vector in which each vector value represents a pixel of the image. I am...