Enhanced Iris Recognition System For Person Identification

In the present work, many methods are combined to build a reliable and fast method for feature extraction in iris recognition system. Reliable techniques for iris image enhancement and circle detection are used. These techniques can then be used to facilitate the further study of the statistics of iris. Also a program coding with MATLAB going through all the stages of the iris recognition is built. It is helpful to understand the procedures of iris recognition and demonstrate the key issues of iris recognition. The Hamming distance has been employed for classification of iris templates, and two templates have been found to match if a test of statistical independence failed. The system performed with perfect recognition and resulted in false accepts and false reject rates of 0.01% and 0.61% respectively. The accuracy of the system is found to be 99.38%. Therefore, iris recognition is reliable and accurate biometric technology.

Gaganpreet Kaur is Assistant Professor in the Department of Computer Science at SGGSWU University,Fatehgarh Sahib, Punjab,India.She has done B.Tech from Kurukshetra University with Honors and M.Tech from Guru Nanak Dev Engineering College, Ludhiana.She is pursuing Ph.D. from Punjab Technical University.She has rich teaching experience of 7 years.