الفهرس 
Chapter (1) IntroductionOnly 14 pages are availabe for public view
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Abstract
Biometric security is new trend in models security systems. Biometrics in general
comprise face, fingerprint, voice, palm print and other types. Traditional biometric
security systems depend on feature extraction from biometrics, and then a feature
matching strategy is applied in the authentication stage.
Unfortunately, Traditional open biometric systems can be hacked, and original
biometrics can be lost forever. That is why the trend of cancelable biometrics thus
evolved as an alternative to open biometric systems. Cancelable biometric systems
depend on the generation of encrypted or distorted versions of the biometrics to be
used instead of the original biometrics in the verification process.
In this thesis, we adapt to strategies to generate cancelable biometric templates. The
first strategy depends on the utilization of the comb digital filters as a tool to distort
the original biometric templates intentionally, while keeping the discrimination ability
between biometrics.
The comb filters are a multi-band filters that induces distortion in the original biometric
templates. The comb filters orders are adapted until the best performance of the
cancelable biometric system is achieved.
On the other hand, the second strategy depends on generating distorted biometric
versions according to the non-invertability of the aliasing effect. First, biometric
patterns are decimated through a down-sampling stage. Hence, the sampling frequency
is lowered beyond the Nyquist rate inducing the aliasing effect.
After that interpolation is performed to maximize the amount of distortion in the
biometric pattern. Polynomial techniques such as bilinear bicubic, cubic spline and
cubic O-MOMS are used in the interpolation process. This strategy guarantees
intended distortion of biometric patterns, while keeping discrimination ability. The
common thread between both proposed strategies is the utilization of digital filtering
in both of them. In the first strategy the comb digital filter with order adaption is used.
On the other hand, the second strategy with Cubic spline and Cubic O-MOMS
interpolation is implemented with digital causal and non-causal filter for digital
interpolation coefficient estimation. Hence, the digital filtering is the heart of both
proposed strategies. Simulation experiments are introduced in this thesis on both face
and fingerprint images.