FPD

Iris recognition is one of the most widely used biometric technologies because of its high reliability and accuracy. While iris recognition usually comprises multiple phases, this paper focuses on two key procedures: iris matching and evaluation. The state-of-the-art of both steps, i.e., Daugman's matching and evaluation algorithms, rely on Hamming Distance. In this paper, we propose a more efficient algorithm based on Frequency-modulated Phase Difference (FPD) in Fourier space. Because FPD is frequency-aware, it effectively detects iris texture landing within particular frequency ranges and significantly improves the matching efficiency. Experiments are carried out on multiple images database showing that FPD is 2.6X faster than Daugman's method while preserving the latter's high accuracy.