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Gabor features have been recognized as one of the best representations for face recognition. Usually, only the magnitudes of the Gabor coefficients are thought of as being useful for face recognition, while the phases of the Gabor features are deemed to be useless and thus usually ignored by face recognition researchers. However, in this paper, our findings show that the latter should be reconsidered. By encoding Gabor phases through local binary patterns and local histograms, we have achieved very impressive recognition results, which are comparable to those of Gabor magnitudes-based methods. The results of our experiments also indicate that, by combining the phases with the magnitudes, higher accuracy can be achieved. Such observations suggest that more attention should be paid to the Gabor phases for face recognition.