A Secure Framework for Protection of Iris Template Using Blockchain

This project presents a system for iris segmentation and classification through a structured workflow involving user registration, dataset handling, and machine learning techniques. The process begins with user registration and login, followed by dataset upload. Once the dataset is uploaded, it undergoes pre-processing to clean and prepare the data for analysis. The workflow is then divided into two phases: training and testing. In the training phase, the model learns from the pre-processed dataset to identify patterns and features. During the testing phase, the trained model is evaluated for its accuracy and reliability. The testing phase includes classification of iris images based on the learned patterns, and finally, the system performs iris segmentation to accurately isolate the iris region from eye images. This end-to-end approach ensures high accuracy in iris recognition tasks, which can be applied in biometric authentication, security systems, and medical diagnostics. The system enhances reliability, efficiency, and automation in iris-based identification. Keywords: Iris segmentation, classification, preprocessing, machine learning, training, testing, biometric authentication, image processing, dataset handling.