Iris Image

Iris image analysis focuses on automatically identifying and analyzing the unique patterns within irises for authentication and other applications. Current research emphasizes improving the robustness and accuracy of iris recognition systems, particularly addressing challenges like cross-device variability, presentation attacks (spoofing), and low-resolution images. This involves employing deep learning architectures such as convolutional neural networks (CNNs), transformers, and generative adversarial networks (GANs), along with advanced techniques like feature fusion and data augmentation. The field's advancements have significant implications for security systems, forensic science, and healthcare, offering enhanced biometric authentication and potentially enabling new diagnostic tools.