Discrete Transforms and Matrix Rotation Based Cancelable Face and Fingerprint Recognition for Biometric Security...

Area of Science:

• Computer Science
• Information Security
• Biometrics

Background:

• Information security is crucial for system success.
• Robust verification mechanisms are needed for data access.
• Cancelable biometrics offer enhanced security and user privacy against attacks.

Purpose of the Study:

• To develop effective methods for generating cancelable biometric templates.
• To ensure revocability and prevent restoration of original biometric data.
• To enhance security and privacy in biometric systems.

Main Methods:

• Utilized discrete transforms: Discrete Fourier Transform (DFT), Fractional Fourier Transform (FrFT), Discrete Cosine Transform (DCT), and Discrete Wavelet Transform (DWT).
• Incorporated matrix rotation in spatial or transform domains to generate distorted templates.
• Combined rotated image versions to prevent original template recovery.

Main Results:

• Proposed methods, particularly those using DCT and DFrFT, demonstrated high efficiency.
• Achieved low Equal Error Rate (EER) and high Area Under the Receiver Operating Characteristic Curve (AROC) values.
• Extensive simulations on face and fingerprint datasets confirmed method effectiveness.

Conclusions:

• The proposed cancelable biometric schemes are highly efficient.
• Achieved an average AROC of 0.998, EER of 0.0023, FAR of 0.008, and FRR of 0.003.
• Comparative analysis validated the superiority of the proposed methods over existing schemes.