Synthetic Iris

Synthetic iris generation focuses on creating realistic artificial iris images using techniques like Generative Adversarial Networks (GANs), often employing architectures such as StyleGAN and Transformer-based models, to address limitations in real-world iris datasets and enhance biometric security systems. Current research emphasizes improving the realism and uniqueness of synthetic irises, minimizing identity leakage from training data, and validating their utility in training iris recognition and presentation attack detection systems. This work is crucial for advancing iris biometrics, particularly by augmenting limited datasets and improving the robustness of iris recognition technologies against attacks.