Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

Discriminative preprocessing of speech : towards improving biometric authentication

Im Rahmen des "SecurePhone-Projektes" wurde ein multimodales System zur Benutzerauthentifizierung entwickelt, das auf ein PDA implementiert wurde. Bei der vollzogenen Erweiterung dieses Systems wurde der Möglichkeit nachgegangen, die Benutzerauthentifizierung durch eine auf biometrischen Parametern (E.: "feature enhancement") basierende Unterscheidung zwischen Sprechern sowie durch eine Kombination mehrerer Parameter zu verbessern. In der vorliegenden Dissertation wird ein allgemeines Bezugssystem zur Verbesserung der Parameter präsentiert, das ein mehrschichtiges neuronales Netz (E.: "MLP: multilayer perceptron") benutzt, um zu einer optimalen Sprecherdiskrimination zu gelangen. In einem ersten Schritt wird beim Trainieren des MLPs eine Teilmenge der Sprecher (Sprecherbasis) berücksichtigt, um die zugrundeliegenden Charakteristika des vorhandenen akustischen Parameterraums darzustellen. Am Ende eines zweiten Schrittes steht die Erkenntnis, dass die Größe der verwendeten Sprecherbasis die Leistungsfähigkeit eines Sprechererkennungssystems entscheidend beeinflussen kann. Ein dritter Schritt führt zur Feststellung, dass sich die Selektion der Sprecherbasis ebenfalls auf die Leistungsfähigkeit des Systems auswirken kann. Aufgrund dieser Beobachtung wird eine automatische Selektionsmethode für die Sprecher auf der Basis des maximalen Durchschnittswertes der Zwischenklassenvariation (between-class variance) vorgeschlagen. Unter Rückgriff auf verschiedene sprachliche Produktionssituationen (Sprachproduktion mit und ohne Hintergrundgeräusche; Sprachproduktion beim Telefonieren) wird gezeigt, dass diese Methode die Leistungsfähigkeit des Erkennungssystems verbessern kann. Auf der Grundlage dieser Ergebnisse wird erwartet, dass sich die hier für die Sprechererkennung verwendete Methode auch für andere biometrische Modalitäten als sinnvoll erweist. Zusätzlich wird in der vorliegenden Dissertation eine alternative Parameterrepräsentation vorgeschlagen, die aus der sog. "Sprecher-Stimme-Signatur" (E.: "SVS: speaker voice signature") abgeleitet wird. Die SVS besteht aus Trajektorien in einem Kohonennetz (E.: "SOM: self-organising map"), das den akustischen Raum repräsentiert. Als weiteres Ergebnis der Arbeit erweist sich diese Parameterrepräsentation als Ergänzung zu dem zugrundeliegenden Parameterset. Deshalb liegt eine Kombination beider Parametersets im Sinne einer Verbesserung der Leistungsfähigkeit des Erkennungssystems nahe. Am Ende der Arbeit sind schließlich einige potentielle Erweiterungsmöglichkeiten zu den vorgestellten Methoden zu finden. Schlüsselwörter: Feature Enhancement, MLP, SOM, Sprecher-Basis-Selektion, SprechererkennungIn the context of the SecurePhone project, a multimodal user authentication system was developed for implementation on a PDA. Extending this system, we investigate biometric feature enhancement and multi-feature fusion with the aim of improving user authentication accuracy. In this dissertation, a general framework for feature enhancement is proposed which uses a multilayer perceptron (MLP) to achieve optimal speaker discrimination. First, to train this MLP a subset of speakers (speaker basis) is used to represent the underlying characteristics of the given acoustic feature space. Second, the size of the speaker basis is found to be among the crucial factors affecting the performance of a speaker recognition system. Third, it is found that the selection of the speaker basis can also influence system performance. Based on this observation, an automatic speaker selection approach is proposed on the basis of the maximal average between-class variance. Tests in a variety of conditions, including clean and noisy as well as telephone speech, show that this approach can improve the performance of speaker recognition systems. This approach, which is applied here to feature enhancement for speaker recognition, can be expected to also be effective with other biometric modalities besides speech. Further, an alternative feature representation is proposed in this dissertation, which is derived from what we call speaker voice signatures (SVS). These are trajectories in a Kohonen self organising map (SOM) which has been trained to represent the acoustic space. This feature representation is found to be somewhat complementary to the baseline feature set, suggesting that they can be fused to achieve improved performance in speaker recognition. Finally, this dissertation finishes with a number of potential extensions of the proposed approaches. Keywords: feature enhancement, MLP, SOM, speaker basis selection, speaker recognition, biometric, authentication, verificatio

Handbook of Vascular Biometrics

This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book

Quaternion Matrices : Statistical Properties and Applications to Signal Processing and Wavelets

Similarly to how complex numbers provide a possible framework for extending scalar signal processing techniques to 2-channel signals, the 4-dimensional hypercomplex algebra of quaternions can be used to represent signals with 3 or 4 components. For a quaternion random vector to be suited for quaternion linear processing, it must be (second-order) proper. We consider the likelihood ratio test (LRT) for propriety, and compute the exact distribution for statistics of Box type, which include this LRT. Various approximate distributions are compared. The Wishart distribution of a quaternion sample covariance matrix is derived from first principles. Quaternions are isomorphic to an algebra of structured 4x4 real matrices. This mapping is our main tool, and suggests considering more general real matrix problems as a way of investigating quaternion linear algorithms. A quaternion vector autoregressive (VAR) time-series model is equivalent to a structured real VAR model. We show that generalised least squares (and Gaussian maximum likelihood) estimation of the parameters reduces to ordinary least squares, but only if the innovations are proper. A LRT is suggested to simultaneously test for quaternion structure in the regression coefficients and innovation covariance. Matrix-valued wavelets (MVWs) are generalised (multi)wavelets for vector-valued signals. Quaternion wavelets are equivalent to structured MVWs. Taking into account orthogonal similarity, all MVWs can be constructed from non-trivial MVWs. We show that there are no non-scalar non-trivial MVWs with short support [0,3]. Through symbolic computation we construct the families of shortest non-trivial 2x2 Daubechies MVWs and quaternion Daubechies wavelets.Open Acces

Identification de personnes par fusion de différentes modalités biométriques

This thesis contributes to the resolution of the problems which are related to the analysis of the biometric data outcome from the iris, the fingerprint and the fusion of these two modalities, for person identification. Thus, after the evaluation of those proposed biometric systems, we have shown that the multimodal biometric system based on iris and fingerprint outperforms both monomodal biometric systems based whatsoever on the iris or on the fingerprint.Cette thèse contribue essentiellement à la résolution des problèmes liés à l'analyse des données biométriques issues de l'iris, de l'empreinte digitale et de la fusion de ces deux modalités pour l'identification de personne. Ainsi, après l'évaluation des trois systèmes biométriques proposés, nous avons prouvé que le système biométrique multimodal basé sur l'iris et l'empreinte digitale est plus performant que les deux systèmes biométriques monomodaux basés que se soit sur l'iris ou sur l'empreinte digitale