Iris recognition: An emerging security environment for human identification

Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification and at the same time, the difficulty in effectively representing such details in an image. Iris is a protected internal organ whose random texture is stable throughout life, it can serve as a kind of living password that one need not remember but one always carries along. Because the randomness of iris patterns has very high dimensionality, recognition decisions are made with confidence levels high enough to support rapid and reliable exhaustive searches through national-sized databases. Iris recognition has shown to be very accurate for human identification. This paper proposes a technique for iris pattern extraction utilizing the graph cut method where the pupilary boundary of the iris is determined. The limbic boundary is identified by adaptive thresholding method. The iris normalization was invariant for translation, rotation and scale after mapping into polar coordinates. The proposed method has an encouraging performance, success rate of localization and normalization and reduces the system operation time. The proposed method involves Graph cut method, Adaptive thresholding, Normalization modules.