Volume IV, Issue VII, July 2015 IJLTEMAS ISSN 2278 - 2540 www.ijltemas.in Page 90 IRIS Recognition by Daugman‟s Method Miss. A. J. Dixit 1 , Mr. K. S. Kazi 2 Department of Electronics & Telecommunication Engineering 1,2 BMIT, Solapur, (M.S.) India 1,2 Abstract- In today’s advanced era it is needed to design the system which will give highly accurate results regarding biometric human identification. Iris recognition is considered to be the best biometric human identification system. Daugman’s method for iris recognition is considered as the efficient & accurate iris recognition system as per previous research. This technique is discussed in detail in this paper. Keywords— Daugman’s Algorithm, Daugman’s Rubber Sheet Model, Hamming Distance, Iris Recognition segmentation, normalization. I. INTRODUCTION n the case of iris recognition as the iris is located at a remote area of eye it is impossible to be copied & main feature of iris is it unique for every individual .Iris pattern of every person is different even the iris of two eyes of the same person are different hence it is ideal feature for recognition. So iris recognition is considered to be most reliable among all existing techniques of biometric recognition. There are many techniques for iris recognition such as by using combined multi scale method, DCT based method, neural network method, eyelash removal method, Daugman‟s method. Among all of these methods we have selected Daugman‟s method for the iris recognition. According to previous research it is considered to be more efficient, accurate & reliable as compared to other existing methods. The concept of the Iris Recognition was firstly proposed by Dr. Frank Burch in the year of 1939. It was successfully implemented in the year of 1990 when Dr. John Daugman created the algorithms for it. II. FEATURES OF IRIS FIG 1: FRONT VIEW OF EYE The iris biometric mainly deals with the identifying a human being by his/her iris pattern extracted from the images of his/her eye. As shown in Figure , the human eye consists of 3 major parts: pupil (the Innermost black part), iris (the Colored part) and sclera (the white part)as shown in fig. The iris and pupil considered to be non concentric. The radius of the inner border of the iris i.e. it‟s border with the pupil is also not constant since the size of pupil increases and decreases depending upon the amount of light incident to the pupil. Every individual in the world has a unique pattern of iris. This pattern can be extracted from the image of the eye and it is encoded. This code can be compared to the codes obtained from the images of 14 other eyes or the same eye. The results of this comparison can represent the amount of difference between the compared codes. In this way it can be concluded if the compared eye patterns belong to the same or different eye. III. FLOWCHART OF IRIS RECOGNITION SYSTEM A. Image Acquisition. It consist of acquisition of a high quality image of the iris with high resolution. It deals with the image capturing rigs. It is needed to obtain images with high resolution with sharpness. It should have proper contrast in the iris pattern with proper illumination. Image should be properly centered. Distance of camera should be up to 3 meter. Image capturing should be accomplished with the help of near infrared camera or LED. CASIA Database The Chinese Academy of Sciences - Institute of Automation (CASIA) eye image database have 756 grayscale images having 108 unique eyes or classes and 7 different images of each unique eye. These images from each class are taken from I