The development of accurate and reliable security systems is a matter of wide interest, and in this context biometrics is seen as a highly effective automatic mechanism for personal identification. Among biometric technologies, IrisCode developed by Daugman in 1993 is regarded as a highly accurate approach, being able to support real-time personal identification of large databases. Since 1993, on the top of IrisCode, different coding methods have been proposed for iris and fingerprint identification. In this research, I extend and generalize IrisCode for real-time secure palmprint identification. PalmCode, the first coding method for palmprint identification developed by me in 2002, directly applied IrisCode to extract phase information of palmprints as features. However, I observe that the PalmCodes from the different palms are similar, having many 45o streaks. Such structural similarities in the PalmCodes of different palms would reduce the individuality of PalmCodes and the performance of palmprint identification systems. To reduce the correlation between PalmCodes, in this thesis, I employ multiple elliptical Gabor filters with different orientations to compute different PalmCodes and merge them to produce a single feature, called Fusion Code. Experimental results demonstrate that Fusion Code performs better than PalmCode. Based on the results of Fusion Code, I further identify that the orientation fields of palmprints are powerful features. Consequently, Competitive Code, which uses real parts of six Gabor filters to estimate the orientation fields, is developed. To embed the properties of IrisCode, such as high speed matching, in Competitive Code, a novel coding scheme and a bitwise angular distance are proposed. Experimental results demonstrate that Competitive Code is much more effective than other palmprint algorithms. Although many coding methods have been developed based on IrisCode for iris and palmprint identification, we lack a detailed analysis of IrisCode. One of the aims of this research is to provide such analysis as a way of better understanding IrisCode, extending the coarse phase representation to a precise phase representation, and uncovering the relationship between IrisCode and other coding methods. This analysis demonstrates that IrisCode is a clustering process with four prototypes; the locus of a Gabor function is a two-dimensional ellipse with respect to a phase parameter and the bitwise hamming distance can be regarded as a bitwise angular distance. In this analysis, I also point out that the theoretical evidence of the imposter binomial distribution of IrisCode is incomplete. I use this analysis to develop a precise phase representation which can enhance iris recognition accuracy and to relate IrisCode and other coding methods. By making use of this analysis, principal component analysis and simulated annealing, near optimal filters for palmprint identification are sought. The near optimal filters perform better than Competitive Code in term of d’ index. Identical twins having the closest genetics-based relationship are expected to have maximum similarity in their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. Palmprint has been studied for personal identification for many years. However, genetically identical palmprints have not been studied. I systemically examine Competitive Code on genetically identical palmprints for automatic personal identification and to uncover the genetically related palmprint features. The experimental results show that the three principal lines and some portions of weak lines are genetically related features but our palms still contain rich genetically unrelated features for classifying identical twins. As biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analyzed before they are massively deployed in security systems. I propose projected multinomial distribution for studying the probability of successfully using brute-force attacks to break into a palmprint system based on Competitive Code. The proposed model indicates that it is computationally infeasible to break into the palmprint system using brute-force attacks. In addition to brute-force attacks, I address the other three security issues: template re-issuances, also called cancellable biometrics, replay attacks, and database attacks. A random orientation filter bank (ROFB) is used to generate cancellable Competitive Codes for templates re-issuances. Secret messages are hidden in templates to prevent replay and database attacks. This technique can be regarded as template watermarking. A series of analyses is provided to evaluate the security levels of the measures.

More and more researchers combine biometrics with passwords and smart cards to design remote authentication schemes for the purpose of high-degree security. However, in most of these authentication schemes proposed in the literatures so far, biometric characteristics are verified in the smart cards only, not in the remote servers, during the authentication processes. Although this kind of design can prevent the biometric data of the users from being known to the servers, it will result in that they are not real three-factor authentication schemes and therefore some security flaws may occur since the remote servers do not indeed verify the security factor of biometrics. In this thesis we propose a truly three-factor remote authentication scheme where all of the three security factors, passwords, smart cards, and biometric characteristics, are examined in the remote servers. Especially, the proposed scheme fully preserves the privacy of the biometric data of every user, that is, the scheme does not reveal the biometric data to anyone else, including the remote servers. Furthermore, we also demonstrate that the proposed scheme is immune to both the replay attacks and the offline-dictionary attacks and it achieves the requirement of low-computation cost for smart-card users. Finally, we give a formal analysis based on the GNY logic to prove that our goals are achieved.

In this thesis work, a detailed analysis of biometric technologies has been done and a new palmprint recognition algorithm has been implemented. The proposed algorithm is based on 2-D Gabor filters. The developed algorithm is first tested on The Hong Kong Polytechnic University Palmprint Database in terms of accuracy, speed and template size. Then a scanner is integrated into the developed algorithm in order to acquire palm images / in this way an online palmprint recognition system has been developed. Then a small palmprint database is formed via this system in Middle East Technical University. Results on this new database have also shown the success of the developed algorithm.

Privacy of personal health records is of ultimate importance. Unfortunately, it is easy to obtain illegal access to electronic health records under insufficient security precautions. Access control based on token or username/password is not adequate for applications in health domain which require heightened security. Currently, electronic signature mechanisms are being employed as a strong alternative to classic methods. In addition, biometrics provide more precise results in comparison to electronic signature methods. However, applicability of biometrics in this field has been prohibited by factors such as the need for special hardware, increased implementation costs, and invasiveness of the biometry sensors (eg. iris topology, fingerprint). Behavioral biometrics such as speech, and keystroke dynamics are easier to implement, and do not suffer from the disadvantages mentioned for the static biometrics. Especially, using keystroke dynamics for user authentication is more advantageous than other advanced biometrics because the implementation is inexpensive and continuous identity control is plausible. The aim of this study is to show the feasibility of merging a biometry-based advanced identity verification method together with an initial access control procedure such as password check. In this study, we provide an authentication framework based on measuring similarity of the typing characteristics of medical reporters, while they are typing medical reports. We have made a prototype of the system and provided classification of keystroke timings for each operator. We have generated a testbed and measured similarity of typing patterns of 5 medical reporters upon typing 4 different kinds of medical reports. Our system performs with hundred percent accuracy in identifying the authorized operators from the reports they type. In current practice, electronic signatures are indispensable for health information systems, but our study shows that keystroke dynamics can easily be included in this chain for increased security.

In this thesis, an audio-video database for speaker recognition is constructed using a digital camcorder. Motion pictures of fifteen hundred speakers are recorded in three different sessions in the database. For each speaker, 20 still images per session are also derived from the video data. It is hoped that this database can provide an appropriate training and testing mechanism for person identification using both voice and face features.

<p>With the advance of the modern information society, the importance of reliable identity authentication has increased dramatically. Using biometrics as a means for verifying the identity of a person increases both the security and the convenience of the systems. By using yourself to verify your identity such risks as lost keys and misplaced passwords are removed and by virtue of this, convenience is also increased. The most mature and well-developed biometric technique is fingerprint recognition. Fingerprints are unique for each individual and they do not change over time, which is very desirable in this application. There are multitudes of approaches to fingerprint recognition, most of which work by identifying so called minutiae and match fingerprints based on these. </p><p>In this diploma work, two alternative methods for locating distinct features in fingerprint images have been evaluated. The Template Correlation Method is based on the correlation between the image and templates created to approximate the homogenous ridge/valley areas in the fingerprint. The high-dimension of the feature vectors from correlation is reduced through principal component analysis. By visualising the dimension reduced data by ordinary plotting and observing the result classification is performed by locating anomalies in feature space, where distinct features are located away from the non-distinct. </p><p>The Circular Sampling Method works by sampling in concentric circles around selected points in the image and evaluating the frequency content of the resulting functions. Each images used here contains 30400 pixels which leads to sampling in many points that are of no interest. By selecting the sampling points this number can be reduced. Two approaches to sampling points selection has been evaluated. The first restricts sampling to occur only along valley bottoms of the image, whereas the second uses orientation histograms to select regions where there is no single dominant direction as sampling positions. For each sampling position an intensity function is achieved by circular sampling and a frequency spectrum of this function is achieved through the Fast Fourier Transform. Applying criteria to the relationships of the frequency components classifies each sampling location as either distinct or non-distinct. </p><p>Using a cyclic approach to evaluate the methods and their potential makes selection at various stages possible. Only the Circular Sampling Method survived the first cycle, and therefore all tests from that point on are performed on thismethod alone. Two main errors arise from the tests, where the most prominent being the number of spurious points located by the method. The second, which is equally serious but not as common, is when the method misclassifies visually distinct features as non-distinct. Regardless of the problems, these tests indicate that the method holds potential but that it needs to be subject to further testing and optimisation. These tests should focus on the three main properties of the method: noise sensitivity, radial dependency and translation sensitivity.</p>

<p>Nowadays biometric identification is used in a variety of applications-administration, business and even home. Although there are a lot of biometric identifiers, fingerprints are the most widely spread due to their acceptance from the people and the cheap price of the hardware equipment. Fingerprint recognition is a complex image recognition problem and includes algorithms and procedures for image enhancement and binarization, extracting and matching features and sometimes classification. In this work the main approaches in the research area are discussed, demonstrated and tested in a sample application. The demonstration software application is developed by using Verifinger SDK and Microsoft Visual Studio platform. The fingerprint sensor for testing the application is AuthenTec AES2501.</p>

<p>In today’s society, people often find themselves in situations where they need to be identified;for example when we buy alcohol, need to use an ATM or log on to our e-mail account. The most common methods today that are used for these kinds of matters are antiquated, and in</p><p>the meantime, criminals all over the world get more sophisticated. Companies invest billions every day in order to protect their interests. Maybe it’s time that we finally give biometrics the</p><p>attention that it deserves.</p><p>This essay aims to describe the biometric methods that are available today, find some of the most effective when it comes to physical access and make a comparison. Face recognition and fingerprint scanning will be described more thoroughly. Pros and cons will be analyzed and the theory will be linked to interviews with three Swedish organisations.</p> / <p>I dagens samhälle hamnar vi människor regelbundet i situationer där vi blir tvungna att identifiera oss. Det kan till exempelvis vara när vi köper alkohol, tar ut pengar eller loggar in på vårt e-mailkonto. De vanligaste metoderna, som idag används för dessa identifieringar, har funnits länge och är föråldrade och i takt med detta blir brottslingar världen allt mer sofistikerade. Dagligen investerar företag världen över miljarder för att skydda exempelvis</p><p>data med hjälp av koder och andra mjukvaruinstallationer. Kanske är det istället dags för att vi ger biometrin en ordentlig chans.</p><p>Den här uppsatsen syftar till att redogöra för de biometriska säkerhetsmetoder som finns tillgängliga, identifiera några av de effektivaste när det gäller fysisk access och jämföra dessa med varandra. Det är framförallt ansiktsigenkänning och fingeravtrycksavläsning som kommer att ges mycket plats i studien. För- och nackdelar kommer att tas upp och teorin kommer att kopplas till intervjuer gjorda med tre svenska företag.</p>

Title from PDF of title page. / Document formatted into pages; contains 115 pages. / Thesis (M.S.C.S.)--University of South Florida, 2003. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: As is seen from the work on gait recognition, there is a de-facto consensus about the silhouette of a person being the low-level representation of choice. It has been hypothesized that the performance degradation that is observed when one compares sequences taken on different surfaces, hence against different backgrounds, or when one considers outdoor sequences is due to the low silhouette quality and its variation. If only one can get better silhouettes the perfomance of gait recognition would be high. This thesis challenges that hypothesis. In the context of the HumanID Gait Challenge problem, we constructed a set of ground truth silhouttes over one gait cycles for 71 subjects, to test recognition across two conditions, shoe and surface. Using these, we show that the performance with ground truth silhouette is as good as that obtained by those obtained by a basic background subtraction algorithm. / ABSTRACT: Therefore further research into ways to enhance silhouette extraction does not appear to be the most productive way to advance gait recognition. We also show, using the manually specified part level silhouettes, that most of the gait recognition power lies in the legs and the arms. The recognition power in various static gait recognition factors as extracted from a single view image, such as gait period, cadence, body size, height, leg size, and torso length, does not seem to be adequate. Using cummulative silhouette error images, we also suggest that gait actually changes when one changes walking surface; in particular the swing phase of the gait gets effected the most. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

As smartphone technology continues to mature, one of the many areas it can help enhance is telemedicine: the concept of using telecommunications to provide health information from a distance. A new medical condition or disease can require frequent visits to the doctor for simple biometric monitoring. These frequent visits are time-consuming and can be extremely inconvenient for the patient. This report describes how a smartphone can be the optimal platform to communicate critical biometric measurements to one's physician, reduce in-person hospital visits, and still allow for the patient to receive feedback from the doctor. A proof-of-concept infrastructure for enabling telemedicine is demonstrated by interfacing a glucose meter with an Android device that uploads that data to the Cloud to be viewed by the doctor. / text