الفهرس 
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Abstract
Reliable automatic recognition of persons has long been an attrac-
tive goal. Much of the work in the eld of biometrics has focused
on identication applications. Iris biometric systems can function as
extremely reliable means of personal identication due to several rea-
sons. The iris is extremely data-rich characteristic trait with unique
non-genetic patterns. Moreover, these patterns are stable throughout
the adult life and are physically protected by the cornea that does not
inhibit external viewability.
The rst -yet critical- step in iris recognition is to isolate the iris
region in the digital image of the eye. This process is called iris lo-
calization and segmentation, and is the focus of this thesis. Di
erent
image processing techniques that involve numerical optimization are
used for iris segmentation and localization.
This thesis reviews and implements di
erent iris localization and
segmentation techniques and compares between them. The iris region
can be approximated as two circles representing iris/pupil boundary
and the iris/sclera boundary. Circular Hough Transform and Integro-
Di
erential operator assume that the iris/pupil and iris/sclera bound-
aries are circular. Active contours, a newly utilized technique in iris
segmentation, attempt to nd the boundaries assuming that they are
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arbitrary by iteratively evolving curves until they lock on nearby edges.
The di
erent iris segmentation techniques are implemented and
tested on database of irises provided by the Chinese Academy of Sci-
ences Institute of Automation (CASIA).
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