Abstract

In this paper, we propose a wavelet based feature extraction method with a high tolerance to white Gaussian noise. This method is also computationally efficient. Along with an HMM classifier, this method is used for face recognition. High recognition rates in the presence of white Gaussian noises with different variances show this technique as a promising feature extraction method.

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