Accelerating Face Biometric Verification Via Quantum PCA and Hybrid Processing
Satinder Pal Singh, Avnish Thakur, Md. Imran Hussain, Moin Hasan · 2025
This paper presents a hybrid classical-quantum algorithm for face biometric verification that enhances the traditional eigenface method using Quantum Principal Component Analysis (QPCA). Classical preprocessing is used for image normalization and mean subtraction, while QPCA performs efficient eigen decomposition of facial data. Quantum projection and similarity measurement are implemented using SWAP test circuits, enabling exponential speedup in highdimensional operations. The proposed system significantly reduces computational complexity, particularly in eigenvalue decomposition, without compromising recognition accuracy. Our implementation demonstrates measurably improved verification performance compared to classical methods, while substantially reducing processing time. Simulation results on reduced-size facial datasets validate the feasibility and computational advantages of our approach. Comparative analysis demonstrates scalability advantages for high-resolution images and large datasets. This work lays a foundation for efficient and secure biometric authentication systems by utilizing the quantum computing advancements.