Aiming at the problem of feature extraction in face recognition, a new feature extraction algorithm based on Gabor is proposed. The Gabor wavelet transform has good extraction and distinction ability and the discriminative advantage of LDA is used to extract features. First, the Gabor wavelet transform is used to extract facial features. Then, PCA is used to reduce the dimension of the obtained high-dimensional features, and LDA is used to reduce the dimension again to obtain the final feature vector. Experiments on ORL and YALE face databases verify the effectiveness of the algorithm.
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