Implementasi Pengenalan Citra Wajah dengan Algoritma Eigenface pada Metode Principal Component Analysis (PCA)

Iwan Setiawan, Welly Iskand, Fauzi Nur Iman, Agustina V Silitonga


The development of image processing technology currently can alleviate human jobs, one of them as the recognition on face. In this study using Principal Component Analysis (PCA) is constructing the input pattern using a digital facial propagation techniques in face recognition. In the construction process pattern and facial recognition start of the object in the form of a face image, detection, construction patterns to be able to determine a new characteristic to proceed facial recognition. The process begins when the facial image have been inputted, then calculated the mean, normalization and covariance matrix, then the program will calculate the eigenvalues and eigenvector followed by calculation Eigenface and PCA feature that will be compared to the image that is on the database. A program will be designed to test some samples of face data to be able to provide a statement of face similarity pattern is being observed

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