Efficient Generation of Cancelable Face Templates Based on Quantum Image Hilbert Permutation

The pivotal need to identify people requires efficient and robust schemes guarantee high levels of personal information security. This paper introduces an encryption algorithm generate cancelable face templates based on quantum image Hilbert permutation. objective is provide sufficient distortion human facial biometrics be stored in a database for authentication requirements through encryption. strength the proposed Cancelable Biometric (CB) scheme guaranteed ability by performing scrambling operation after addition noise mask with pre-specified variance initial seed. Generating depends strategy three basic steps: Initialization, Odd module, Even module. Notably, achieves recognition rates Area under Receiver Operating Characteristic (AROC) curve, value up 99.51%. Furthermore, comparisons state-of-the-art are performed validate scheme.