Abstract

Human face recognition is currently a very active research area with focus on ways to perform robust biometric identification. Many face recognition algorithms have been proposed, among the different approaches, frequency domain methods, like advanced correlation filters have been shown to exhibit better tolerance to illumination variations than traditional methods. In this paper, we propose a new frequency domain face recognition method which combines the Gabor transforms and a quaternion correlation filter for face recognition when the illumination conditions are changed. The Gabor transform provides optimally localized spatial and frequency domain representation of the original face images, and the quaternion correlation filters can jointly process multi-channel subbands for more robust face recognition. The numerical experiments show that the proposed method outperforms the previously compared advanced correlation filter methods.

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