19 research outputs found
Advancing iris biometric technology
PhD ThesisThe iris biometric is a well-established technology which is already in use in
several nation-scale applications and it is still an active research area with several
unsolved problems. This work focuses on three key problems in iris biometrics
namely: segmentation, protection and cross-matching. Three novel
methods in each of these areas are proposed and analyzed thoroughly.
In terms of iris segmentation, a novel iris segmentation method is designed
based on a fusion of an expanding and a shrinking active contour by integrating
a new pressure force within the Gradient Vector Flow (GVF) active
contour model. In addition, a new method for closed eye detection is proposed.
The experimental results on the CASIA V4, MMU2, UBIRIS V1 and
UBIRIS V2 databases show that the proposed method achieves state-of-theart
results in terms of segmentation accuracy and recognition performance
while being computationally more efficient. In this context, improvements
by 60.5%, 42% and 48.7% are achieved in segmentation accuracy for the
CASIA V4, MMU2 and UBIRIS V1 databases, respectively. For the UBIRIS
V2 database, a superior time reduction is reported (85.7%) while maintaining
a similar accuracy. Similarly, considerable time improvements by 63.8%,
56.6% and 29.3% are achieved for the CASIA V4, MMU2 and UBIRIS V1
databases, respectively.
With respect to iris biometric protection, a novel security architecture is designed
to protect the integrity of iris images and templates using watermarking
and Visual Cryptography (VC). Firstly, for protecting the iris image, text
which carries personal information is embedded in the middle band frequency
region of the iris image using a novel watermarking algorithm that randomly
interchanges multiple middle band pairs of the Discrete Cosine Transform
(DCT). Secondly, for iris template protection, VC is utilized to protect the
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iris template. In addition, the integrity of the stored template in the biometric
smart card is guaranteed by using the hash signatures. The proposed method
has a minimal effect on the iris recognition performance of only 3.6% and
4.9% for the CASIA V4 and UBIRIS V1 databases, respectively. In addition,
the VC scheme is designed to be readily applied to protect any biometric binary
template without any degradation to the recognition performance with a
complexity of only O(N).
As for cross-spectral matching, a framework is designed which is capable of
matching iris images in different lighting conditions. The first method is designed
to work with registered iris images where the key idea is to synthesize
the corresponding Near Infra-Red (NIR) images from the Visible Light (VL)
images using an Artificial Neural Network (ANN) while the second method
is capable of working with unregistered iris images based on integrating the
Gabor filter with different photometric normalization models and descriptors
along with decision level fusion to achieve the cross-spectral matching. A
significant improvement by 79.3% in cross-spectral matching performance is
attained for the UTIRIS database. As for the PolyU database, the proposed
verification method achieved an improvement by 83.9% in terms of NIR vs
Red channel matching which confirms the efficiency of the proposed method.
In summary, the most important open issues in exploiting the iris biometric
are presented and novel methods to address these problems are proposed.
Hence, this work will help to establish a more robust iris recognition system
due to the development of an accurate segmentation method working for iris
images taken under both the VL and NIR. In addition, the proposed protection
scheme paves the way for a secure iris images and templates storage.
Moreover, the proposed framework for cross-spectral matching will help to
employ the iris biometric in several security applications such as surveillance
at-a-distance and automated watch-list identification.Ministry of Higher Education and
Scientific Research in Ira
Dynamical Systems
Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...
Modeling and Simulation in Engineering
The general aim of this book is to present selected chapters of the following types: chapters with more focus on modeling with some necessary simulation details and chapters with less focus on modeling but with more simulation details. This book contains eleven chapters divided into two sections: Modeling in Continuum Mechanics and Modeling in Electronics and Engineering. We hope our book entitled "Modeling and Simulation in Engineering - Selected Problems" will serve as a useful reference to students, scientists, and engineers
Mixing Biometric Data For Generating Joint Identities and Preserving Privacy
Biometrics is the science of automatically recognizing individuals by utilizing biological traits such as fingerprints, face, iris and voice. A classical biometric system digitizes the human body and uses this digitized identity for human recognition. In this work, we introduce the concept of mixing biometrics. Mixing biometrics refers to the process of generating a new biometric image by fusing images of different fingers, different faces, or different irises. The resultant mixed image can be used directly in the feature extraction and matching stages of an existing biometric system. In this regard, we design and systematically evaluate novel methods for generating mixed images for the fingerprint, iris and face modalities. Further, we extend the concept of mixing to accommodate two distinct modalities of an individual, viz., fingerprint and iris. The utility of mixing biometrics is demonstrated in two different applications. The first application deals with the issue of generating a joint digital identity. A joint identity inherits its uniqueness from two or more individuals and can be used in scenarios such as joint bank accounts or two-man rule systems. The second application deals with the issue of biometric privacy, where the concept of mixing is used for de-identifying or obscuring biometric images and for generating cancelable biometrics. Extensive experimental analysis suggests that the concept of biometric mixing has several benefits and can be easily incorporated into existing biometric systems
Enabling and Understanding Failure of Engineering Structures Using the Technique of Cohesive Elements
In this paper, we describe a cohesive zone model for the prediction of failure of engineering solids and/or structures. A damage evolution law is incorporated into a three-dimensional, exponential cohesive law to account for material degradation under the influence of cyclic loading. This cohesive zone model is implemented in the finite element software ABAQUS through a user defined subroutine. The irreversibility of the cohesive zone model is first verified and subsequently applied for studying cyclic crack growth in specimens experiencing different modes of fracture and/or failure. The crack growth behavior to include both crack initiation and crack propagation becomes a natural outcome of the numerical simulation. Numerical examples suggest that the irreversible cohesive zone model can serve as an efficient tool to predict fatigue crack growth. Key issues such as crack path deviation, convergence and mesh dependency are also discussed