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Due to increasing applications which need security, face is the most natural way to recognize the person. This paper presents the performance analysis of different face recognition techniques. Linear Binary Pattern (LBP), Gabor Wavelet, Histogram of Oriented Gradient (HOG) techniques are used for feature extraction on two standard databases of images i.e., ORL and Yale Face database. Then Principal Component Analysis (PCA) is applied for feature selection with six different distance metric functions, Cosine, Euclidean, Correlation, Cityblock, Spearman and Minkowski for similarity matching of images.