Advancements In Iris Recognition Techniques For Biometric Authentication Systems

Abstract

The increasing demand for secure and reliable biometric authentication systems has led to significant advancements in iris recognition techniques. Iris recognition, owing to its high accuracy and unique features, has emerged as a preferred modality for identity verification. This paper provides a comprehensive overview of recent advancements in iris recognition technology, emphasizing the enhancements in image acquisition, feature extraction, and matching algorithms. We discuss the integration of deep learning approaches, which have substantially improved the robustness and accuracy of iris recognition systems. Furthermore, we explore the development of multimodal biometric systems that combine iris recognition with other biometric modalities to enhance security and user convenience. The challenges associated with iris recognition, including spoofing attacks, occlusions, and varying lighting conditions, are also examined. This paper aims to highlight the potential of cutting-edge iris recognition techniques in revolutionizing biometric authentication systems, particularly in high-security environments. Our findings indicate that continuous innovations and research in this field are crucial for addressing current limitations and advancing the capabilities of biometric authentication systems.