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A Secure Face Recognition Algorithm Based on Adaptive Non-uniform Quantization

机译:一种基于自适应非均匀量化的安全面识别算法

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With the development of face recognition technology, some privacy and security problems arise. Principal component analysis (PCA); is one of the popular approaches for face recognition. Aiming at the leakage for the security of PCA, this paper proposes a secure face recognition algorithm based on adaptive non-uniform quantization (ANUQ) which quantizes the template feature obtained by PCA and stores the hash value of the quantization feature instead of the template feature. Experimental results show this algorithm improves the security of the system while the accuracy is the same as PCA.
机译:随着人脸识别技术的发展,出现了一些隐私和安全问题。主成分分析(PCA);是面部识别的流行方法之一。本文旨在泄漏PCA的安全性,提出了一种基于自适应非均匀量化(ANUQ)的安全面部识别算法,其量化PCA获得的模板特征,并存储量化特征的散列值而不是模板特征。实验结果表明,该算法提高了系统的安全性,而准确性与PCA相同。

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