A o el uman Identifier System usin Retina Ima e and u y Clusterin

What is important for an identification system is to be accurate, low cost, fast, and safe. Almost all current identification methods such as fingerprint, face, hand palm and ir is recognition, are vulnerable considering plastic surgeries and some other changes in face, palm and finger print, while this is not the case for the retina. Human retina would never change during ones life and thus the uni ueness of the retina blood vessels pattern is the most accurate pattern among other biometric systems. In this paper, we present a new approach for human identification using retina recognition and fuzzy C means clustering algorithm. This method is insensitive to rotation, rescaling and transformation. The Fourier Mellin transform coefficients and moments of the retinal image have been used as features extracted in our system. To compensate the rotational effects of the retinal scanner, a rotation compensator was designed. For optic disc localization, the Haar wavelet and snakes model have been used. The experimental results show an error rate close to zero for the propose method.