Study of iris recognition using human visual system based methods

Abstract

Iris recognition using methods inspired by the human visual system represents a cutting-edge approach in biometric identification. By analyzing key stages such as detection, normalization, feature extraction, and classification, this study demonstrates how techniques like edge detection, Gabor filters, and wavelet transforms can significantly enhance recognition accuracy and robustness. Additionally, the exploration of FPGA technology provides a pathway for efficient hardware implementation. The findings contribute to advancing iris recognition systems by integrating theoretical frameworks with practical applications.