Iris Recognition is one of the most biometric identification systems that identify people based on their iris. In this paper the iris recognition system is implemented by using Hough Transform and Canny edge detection techniques. In this paper the iris recognition via many steps, these steps are image acquisition, edge detection, localization, feature extraction, and matching. Two types of extractions: eight sub-images and sixteen sub-images are used to divide the iris images. The implemented system uses CASIA iris database. This paper provides an efficient iris identification system and the software to perform this research developed using the Matlab programming language.
Title = "Comparison of Feature Extractions for Iris Recognition",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "7",
Pages ="411 - 478",
Year = "2018",
Authors ="Ei Ei Soe, Aye Kyi Pyar Shwe, Ei Ei Myat"}