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An Improved Face Recognition System Using PCA and KNN

M. J. Parseh, P. Jafari


In this paper, we improve a face recognition system using Principal Component Analysis (PCA) to extract features from the face images and reduce the dimensionality of each image and K nearest neighbor to classify data. Both methods have been used together to have the most accuracy. Experiments have been carried on Olivetti Research Laboratory Human Face Database (ORL). Face images are in grayscale and in different poses. Results that have been calculated and shown in the last section, illustrates the improvement of our proposed method.


Face Recognition, Principal Component Analysis (PCA), K-Nearest Neighbour (KNN).

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