Iris Recognition Optimized for Information Assurance

In an increasingly digital society, the demand for secure identification has led to increased development of biometric systems. These biometric systems are becoming widely adopted and accepted as one of the most effective ways to positively identify people. We discuss the history, purpose, and nature of both physiological and behavioral biometric systems and how they are classified. Some common biometric systems include fingerprinting, signatures, and face recognition. However, iris recognition is the most reliable of the biometric systems used today, in many respects. In this project, we examined the properties and implementation of iris recognition biometric systems. A general iris recognition system consists of five parts: 1) image acquisition, In which a picture of the eye is acquired. 2) Segmentation, which locates the borders of the iris in the image. 3) Normalization, which maps the circular iris to a rectangular image. 4) Feature encoding, which creates a biometric template. 5) Matching, which is the process of comparing templates. The mathematics of each of these parts is described in detail and several implementations of these methods are mentioned. It is important to note that one particular algorithm for e.g. feature encoding is not superior to another, as different algorithms can be customized for a particular application area. Specifically, we examine such differences by applying an open-source MATLAB package for iris recognition to the iris image database maintained by the Chinese Academy of Sciences. Keywords: iris, biometric, identification, security because every human eye has unique features in the iris which are different from every other iris, which allows a person to be identified by patterns within the iris. The method involves taking pictures of a subject’s eye, finding the iris, converting the iris portion of the image into digital form, and writing sophisticated computer software to compare iris patterns and determine if a subject is who he/she claims to be. Compared to other biometrics, iris recognition boasts the lowest rates for false identification. Thus, iris recognition is ideal for tasks that require a very high level of security

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