to download project abstract


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 recognize 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 pattern namely, 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 Eigen faces was formed (face space) by
finding the eigenvector corresponding to the largest eigenvalue of the face image. The area of
this project face detection system with face recognition is Image processing. The software
requirements for this project is matlab software.
Keywords: face detection, Eigen face, PCA, matlab

Extension: There are vast number of applications from this face detection project, this project
can be extended that the various parts in the face can be detect which are in various directions
and shapes.

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