Optimized Features Extraction of IRIS Recognition by Using MADLA to Ensure Secure Authentication

Abstract

Nowadays, Iris recognition is a method of biometric verification of the person authentication process based on the human iris unique pattern, which is applied to control system for high level security. It is a popular system for recognizing humans and essential to understand it. The objective of this method is to assign a unique subject for each iris image for authentication of the person and provide an effective feature representation of the iris recognition with the image analysis. This paper proposed a new optimization and recognition process of iris features selection by using proposed Modified ADMM and Deep Learning Algorithm (MADLA). For improving the performance of the security with feature extraction, the proposed algorithm is designed and used to extract the strong features identification of iris of the person with less time, better accuracy, improving performance in access control and in security level. The evaluations of iris data are demonstrated the improvement of the recognition accuracy. In this proposed methodology, the recognition of the iris features has been improved and it incorporates into the iris recognition systems.