Iris Detection and Authentication System Using Deep Learning Techniques

Abstract

A biometric modality for individual identification, iris recognition is very reliable because human iris patterns are stable and distinctive. An overview of a unique deep learning method for iris recognition and authentication using convolutional neural networks (CNN) is provided in this abstract. The suggested approach provides a reliable and safe means of personal verification by utilizing Convolutional neural networks to extract complex information from iris pictures. The first step in the iris identification procedure is to get a person's iris image, which is usually done with the use of specialist iris imaging equipment. To improve the clarity of the iris pattern and reduce noise, the obtained iris picture is pre-processed. To generate a uniform template for additional processing, the iris region is then separated and isolated from the remainder of the picture. Using Convolutional neural network deep learning for iris detection has several benefits, such as high accuracy, resilience to spoof attacks, and adaptability to changes in illumination and pupil dilation. Applications like financial transactions, border security, and secure access management are just a few of the areas in which technology excels.