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The binary quantization method which is used in random projection based biometric hashing systems reduces the authentication performance of these systems. In this paper, we propose new statistical quantization methods for biometric hashing systems. Our proposed quantization methods use Gaussian mixture model and Gaussian distributions to determine quantization threshold value. Therefore, we improve the authentication performance of the biometric hashing systems with our proposed quantization methods. We also provide experimental results of the proposed methods. The experiments are achieved on the AT&T face database, comprising 400 face images from 20 subjects.