IRIS Recognition Using Deep Learning Technique

Biometric authentication has become an essential technology for secure identification systems. Among various biometric methods, iris recognition is considered one of the most reliable and accurate techniques due to the uniqueness and stability of iris patterns. This paper presents an iris recognition system using machine learning techniques for secure and efficient identity verification. The proposed system captures iris images, preprocesses them to remove noise, segments the iris region, and extracts unique features for classification. Machine learning algorithms are used to analyze the iris patterns and match them with stored templates in a database. The system ensures high accuracy, reliability, and security compared to traditional authentication methods such as passwords or PINs. Iris recognition systems can be applied in various fields including banking security, border control, mobile authentication, and access control systems. The proposed model aims to improve recognition accuracy and enhance security in biometric identification systems.