FACE RECOGNITION SYSTEMHARDWARE SPECIFICATIONProcessor: Pentium IV 2.4 GHz Hard Disk: 80 GB RAM: 256 MBMonitor: 17 Samsung MonitorKeyboard: 104 KeysMouse: Genius (Optical Mouse)SOFTWARE SPECIFICATIONOperating System: Windows XP and aboveFront end: VB.NetBack end: Ms-AccessEXISTING SYSTEMFacial recognition systems are computer based security systems that are able to automatically detect and identify human faces. These systems depend on a recognition algorithm. But the most of the algorithm considers somewhat global data patterns while recognition process. This will not yield accurate recognition system. Less accurate. Does not deal with manifold structure. It does not deal with biometric characteristics.DRAWBACKS OF EXISTING SYSTEMThe existing system is not user friendly because the retrieval of data is very slow and data is not maintained efficiently. Every work is done manually so user cannot generate report in the middle of the requirement because it is very time consuming. The drawbacks of existing systems can be summarized as Error prone Does not prevent cheating At the mercy of person in charge No assurance of individual identify

PROPOSED SYSTEMThe proposed system makes use of principle component analysis method, which is cluster analysis tool. It is designed to capture the variance in data set in terms of principle components. In effect one trying to reduce the dimensionality of data. One approach to copying with the problem of excessive dimensionality by combining features. PCA aims to extract subspace in which variance is maximized. The output set of normal vector is representing the Eigen vectors of sample covariance matrix associated with largest Eigen values. This principle is implemented with unsupervised learning concept with training and test data. The advantages can be summarized as: Error free Cannot be faked Highly secure No personal bias can be intervened

FEATURES OF PROPOSED SYSTEM The need is to develop the existing system into a system which is more accurate and perfect in identifying the faces. The existing algorithm had complex calculations. So the new proposed technique is simpler and gives accurate results. Computer operator control will be no chance of occurring errors. Moreover storing and retrieving images is faster than the existing system. Work can be done speedily and in time. Quick response time Errors can be avoided User linking for a GUI based softwareMODULE DESCRIPTIONAnalyzed and conclude that project can be implemented using major modules:- Face Enrollment Face Recognition Face Database List Face EnrollmentA new face can be added by the user into face space database. The photo and the information about the photo are stored into the database. Face Recognition Compares a person faces with all the images in database and choose the closest match. Here principle component analysis is performed with training data set. The result is performed test data set. Face Database ListDisplay all the faces and its templates in the database. Admin can view the stored faces and can alter it any time.