الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
The iris is a physiological feature that possesses genetic independence and contains extremely information-rich physical structure and unique texture pattern. The iris is highly complex enough to be used as a biometric signature. Statistical analysis reveals that the iris is the most mathematically unique feature of the human body because of the hundreds of degrees of freedom, it gives and the ability to accurately measure its texture. The minute details of the iris texture are believed to be determined randomly during the fetal development of the eye. They are also believed to be different between persons and between the left and right eye of the same person. The color of the iris can change as the amount of pigment in the iris increases during childhood. Nevertheless, for most of a human’s lifespan, the appearance of the iris is relatively constant. Among the different biometrics, iris recognition has the following advantages: Iris is very unique, even identical twins have highly different irises; Iris is well protected inside the eye, so it is unlikely to get physically damaged and it is also hard for an impostor to fool the system; Iris recognition is more hygienic even if the system is to be used by a large number of people because it does not involve physical contact
Thesis Contributions: The major contributions of this thesis can be described as follows:
1. The development of a mathematical model of the geometric uniqueness of the iris inner and outer boundaries.
2. The study of the iris texture feature uniqueness of different region of interest of an iris.
3. The introduction of a simple, fast, and efficient iris texture feature bipolar encoding by using Hilbert transform
We presented a comprehensive mathematical formulation of this idea and indicated the connection between the Fourier transform and Hilbert transform as related to analytic signals.
A comprehensive review of Hilbert transform properties with their proofs is presented. The properties of the analytic signal as related to the Hilbert transform are proved and presented. An error analysis of representing a real signal by an analytic one is also presented. This information form the basis of the iris texture binary encoding technique proposed in the thesis. The proposed iris texture binary encoding process is introduced and the idea is utilized for recovering phase information from strong analytic signal. The process is analyzed and justified on a synthetic example.