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The face is one of the easiest ways to distinguish the individual identity of each other. Face recognition is
a personal identification system that uses personal characteristics of a person to identify the person's identity.
Human face recognition procedure basically consists of two phases, namely face detection, where this process takes
place very rapidly in humans, except under conditions where the object is located at a short distance away, the next
is the introduction, which recognizes a face as individuals. Stage is then replicated and developed as a model for
facial image recognition (face recognition) is one of the much-studied biometrics technology and developed by
experts. There are two kinds of methods that are currently popular in developed face recognition patterns, namely,
the Eigenface method and Fisherface method. Facial image recognition Eigenface method is based on the
reduction of face dimensional space using Principal Component Analysis (PCA) for facial features. The main
purpose of the use of PCA on face recognition using Eigenfaces was formed (face space) by finding the eigenvector
corresponding to the largest eigenvalue of the face image. The area of this project's face detection system with face
recognition is Image processing. The software requirements for this project is matlab software.
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