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Signal Processing Methodologies for Resource-efficient and Secure Communications in Wireless NetworksBui, Francis Minhthang 15 July 2009 (has links)
Future-generation wireless and mobile networks are expected to
support a panoply of multimedia services, ranging from voice to
video data. There is also a de facto "anytime anywhere"
mentality that reliable communications should be ubiquitously
guaranteed, irrespective of temporal or geographical
constraints. However, the implicit catch is that these
specifications should be achieved with only minimal
infrastructure expansion or cost increases. In this thesis,
various signal processing methodologies conducive to attaining
these goals are presented.
First, a system model that takes into account the time-varying
nature of the mobile environment is developed. To this end, a
mathematically tractable basis-expansion model (BEM) of the
communication channel, augmented with multiple-state
characterization, is proposed. In the context of the developed
system model, strategies for enhancing the quality of service
(QoS), while maintaining resource efficiency, are then studied.
Specifically, dynamic channel tracking, adaptive modulation and
coding, interpolation and random sampling, and spatiotemporal
processing are examined as enabling solutions. Next, the
question of how to appropriately aggregate these disparate
methods is recast as a nonlinear constrained optimization
problem. This enables the construction of a flexible framework
that can accommodate a wide range of applications, to deliver
practical network designs. In particular, the developed methods
are well-suited for multi-user communication systems,
implemented using spread-spectrum and multi-carrier solutions,
such as code division multiple access (CDMA) and orthogonal
frequency division multiplexing (OFDM).
Moreover, privacy and security requirements are increasingly
becoming essential aspects of the QoS paradigm in
communications. Combined with the advent of novel security
technologies, such as biometrics, the conventional
communication infrastructure is expected to undergo fundamental
modifications to support these new system components and
modalities. Therefore, within the same framework for maximizing
resource efficiency, several unique signal processing
applications in network security using biometrics are also
investigated in this thesis. It is shown that a resource
allocation approach is equally appropriate, and productive, in
delivering efficient and practical key distribution and
biometric encryption solutions for secure communications.
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Signal Processing Methodologies for Resource-efficient and Secure Communications in Wireless NetworksBui, Francis Minhthang 15 July 2009 (has links)
Future-generation wireless and mobile networks are expected to
support a panoply of multimedia services, ranging from voice to
video data. There is also a de facto "anytime anywhere"
mentality that reliable communications should be ubiquitously
guaranteed, irrespective of temporal or geographical
constraints. However, the implicit catch is that these
specifications should be achieved with only minimal
infrastructure expansion or cost increases. In this thesis,
various signal processing methodologies conducive to attaining
these goals are presented.
First, a system model that takes into account the time-varying
nature of the mobile environment is developed. To this end, a
mathematically tractable basis-expansion model (BEM) of the
communication channel, augmented with multiple-state
characterization, is proposed. In the context of the developed
system model, strategies for enhancing the quality of service
(QoS), while maintaining resource efficiency, are then studied.
Specifically, dynamic channel tracking, adaptive modulation and
coding, interpolation and random sampling, and spatiotemporal
processing are examined as enabling solutions. Next, the
question of how to appropriately aggregate these disparate
methods is recast as a nonlinear constrained optimization
problem. This enables the construction of a flexible framework
that can accommodate a wide range of applications, to deliver
practical network designs. In particular, the developed methods
are well-suited for multi-user communication systems,
implemented using spread-spectrum and multi-carrier solutions,
such as code division multiple access (CDMA) and orthogonal
frequency division multiplexing (OFDM).
Moreover, privacy and security requirements are increasingly
becoming essential aspects of the QoS paradigm in
communications. Combined with the advent of novel security
technologies, such as biometrics, the conventional
communication infrastructure is expected to undergo fundamental
modifications to support these new system components and
modalities. Therefore, within the same framework for maximizing
resource efficiency, several unique signal processing
applications in network security using biometrics are also
investigated in this thesis. It is shown that a resource
allocation approach is equally appropriate, and productive, in
delivering efficient and practical key distribution and
biometric encryption solutions for secure communications.
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Research on Identification of Laser Speckles and SignalsYeh, Jin-Wei 07 September 2010 (has links)
With an increasing emphasis on personal privacy, security, and convenience, the
security of identification system is an important issue nowadays. In this thesis, two
intelligent identification systems, laser speckle image identification system and
laser-based finger biometric system, are proposed to perform superior solutions for
identification applications. In laser speckle image identification system, we
investigated the characteristics of laser speckle as well as proposed an appropriate
algorithm to establish this system. The proposed algorithm is a coarse-to-fine process
which identifies laser speckle images systematically. In laser-based finger biometric
system, a new biometric approach is described to proceed personal identification
using a scanner with a low power laser scans across the surface of the finger and
continuously recording the reflected intensity at a fixed position. Experimental results
show that the recognition rates of the proposed system are both 100%.
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Research on Identification and Analysis of Optoelectronic Sensor Fingerprint SignalsJhang, Yan-Hao 10 September 2012 (has links)
In this thesis, we proposed an innovation ideal that is employment of laser to extract finger feature, and constructed laser speckle recognition systems for this kind of feature. When projecting laser on the object surface, the speckle could be obtained to represent the characteristic of object surface by collecting scattered light. Two measurement of scattered light was adopted. First is laser signal recording the strength of scattered light when laser scan across the finger. The second is laser speckle image which is demonstrated when projecting the laser on the fingerprint and simultaneously collecting the scatter light by CCD. We proposed two recognition systems for laser signal and laser speckle. Besides, the proposed laser speckle fingerprint recognition system combines biometric detection, it can accurately distinguish biometric and non-biometric speckle. Experimental results demonstrate that proposed laser speckle recognition systems are feasible and with excellent ability of identity verification.
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CMOS fingerprint sensor electrostatic modelingSoora, Praveen K., January 2000 (has links)
Thesis (M.S.)--West Virginia University, 2000. / Title from document title page. Document formatted into pages; contains viii, 94 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 88-89).
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User perception related to identification through biometrics within electronic businessGiesing, Ilse. January 2003 (has links)
Thesis (M.Com.)(Informatics)--University of Pretoria, 2003. / Includes bibliographical references.
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A method for human identification using static, activity-specific parametersJohnson, Amos Y., Jr. 05 1900 (has links)
No description available.
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Plant species biometric using feature hierarchiesPahalawatta, Kapila January 2008 (has links)
Biometric identification is a pattern recognition based classification system that recognizes an individual by determining its authenticity using a specific physiological or behavioural characteristic (biometric). In contrast to number of commercially available biometric systems for human recognition in the market today, there is no such a biometric system for plant recognition, even though they have many characteristics that are uniquely identifiable at a species level. The goal of the study was to develop a plant species biometric using both global and local features of leaf images. In recent years, various approaches have been proposed for characterizing leaf images. Most of them were based on a global representation of leaf peripheral with Fourier descriptors, polygonal approximations and centroid-contour distance curve. Global representation of leaf shapes does not provide enough information to characterise species uniquely since different species of plants have similar leaf shapes. Others were based on leaf vein extraction using intensity histograms and trained artificial neural network classifiers. Leaf venation extraction is not always possible since it is not always visible in photographic images. This study proposed a novel approach of leaf identification based on feature hierarchies. First, leaves were sorted by their overall shape using shape signatures. Then this sorted list was pruned based on global and local shape descriptors. The consequent biometric was tested using a corpus of 200 leaves from 40 common New Zealand broadleaf plant species which encompass all categories of local information of leaf peripherals. Two novel shape signatures (full-width to length ratio distribution and half-width to length ratio distribution) were proposed and biometric vectors were constructed using both novel shape signatures, complex-coordinates and centroid-distance for comparison. Retrievals were compared and the biometric vector based on full-width to length ratio distribution was found to be the best classifier. Three types of local information of the leaf peripheral (leaf margin coarseness, stem length to blade length ratio and leaf tip curvature) and the global shape descriptor, leaf compactness, were used to prune the list further. The proposed biometric was able to successfully identify the correct species for 37 test images (out of 40). The proposed biometric identified all the test images (100%) correctly if two species were returned compared to the low recall rates of Wang et al. (2003) (30%, if 10 images were returned) and Ye et al. (2004) (71.4%, if top 5 images were returned). The biometric can be strengthened by adding reference images of new species to the database, or by adding more reference images of existing species when the reference images are not enough to cover the leaf shapes.
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Face recognition with Eigenfaces : a detailed study.Vawda, Nadeem. January 2012 (has links)
With human society becoming increasingly computerised, the use of biometrics to automatically
establish the identity of an individual is of great interest in a wide variety of
applications. Facial appearance is an appealing biometric, on account of its relatively
non-intrusive nature. As such, automated face recognition systems have been the subject
of much research in recent years.
This dissertation describes the development of a fully automatic face recognition
system, and provides an analysis of its performance under various di erent operating
conditions, in comparison with results published in prior literature. In addition to giving
a detailed description of the mathematical underpinnings of the techniques used by the
system, we discuss the practical considerations involved in implementing the described
techniques.
The system presented here uses the eigenface approach to representing facial features.
A number of di erent recognition techniques have been implemented and evaluated.
These include a number of variants of the original eigenface technique proposed by
Turk and Pentland, as well as a related technique based on the probabilistic approach of
Moghaddam et al.
Due to the wide range of datasets used to evaluate face recognition systems in
the literature, it is di cult to reliably compare the performance of di erent systems. The
system described here has been tested with datasets encompassing a wide range of di erent
conditions, allowing us to draw conclusions about how the characteristics of the test data
a ect the results that are obtained.
The performance of this system is comparable to other eigenface-based systems
documented in the literature, achieving success rates in the region of 85% for large datasets
under controlled conditions. However, performance was observed to degrade signi cantly
when testing with more free-form images; in particular, the e ects of ageing on facial
appearance were noted to cause problems for the system. This suggests that the matter
of ageing is still a fruitful direction for further research. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2012.
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Automated face detection and recognition for a login system /Louw, Lloyd A. B. January 2007 (has links)
Thesis (MScIng)--University of Stellenbosch, 2007. / Bibliography. Also available via the Internet.
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