Fingerabdruckswachstumvorhersage, Bildvorverarbeitung und Multi-level Judgment Aggregation

Im ersten Teil dieser Arbeit wird Fingerwachstum untersucht und eine Methode zur Vorhersage von Wachstum wird vorgestellt. Die Effektivität dieser Methode wird mittels mehrerer Tests validiert. Vorverarbeitung von Fingerabdrucksbildern wird im zweiten Teil behandelt und neue Methoden zur Schätzung des Orientierungsfelds und der Ridge-Frequenz sowie zur Bildverbesserung werden vorgestellt: Die Line Sensor Methode zur Orientierungsfeldschätzung, gebogene Regionen zur Ridge-Frequenz-Schätzung und gebogene Gabor Filter zur Bildverbesserung. Multi-level Jugdment Aggregation wird eingeführt als Design Prinzip zur Kombination mehrerer Methoden auf mehreren Verarbeitungsstufen. Schließlich wird Score Neubewertung vorgestellt, um Informationen aus der Vorverarbeitung mit in die Score Bildung einzubeziehen. Anhand eines Anwendungsbeispiels wird die Wirksamkeit dieses Ansatzes auf den verfügbaren FVC-Datenbanken gezeigt.Finger growth is studied in the first part of the thesis and a method for growth prediction is presented. The effectiveness of the method is validated in several tests. Fingerprint image preprocessing is discussed in the second part and novel methods for orientation field estimation, ridge frequency estimation and image enhancement are proposed: the line sensor method for orientation estimation provides more robustness to noise than state of the art methods. Curved regions are proposed for improving the ridge frequency estimation and curved Gabor filters for image enhancement. The notion of multi-level judgment aggregation is introduced as a design principle for combining different methods at all levels of fingerprint image processing. Lastly, score revaluation is proposed for incorporating information obtained during preprocessing into the score, and thus amending the quality of the similarity measure at the final stage. A sample application combines all proposed methods of the second part and demonstrates the validity of the approach by achieving massive verification performance improvements in comparison to state of the art software on all available databases of the fingerprint verification competitions (FVC)

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

Statistical Modelling of Fingerprints

It is believed that fingerprints are determined in embryonic development. Unlike other personal characteristics the fingerprint appears to be a result of a random process. For example fingerprints of identical twins (whose DNA is identical) are distinct, and extensive studies have found little evidence of a genetic relationship in terms of types of fingerprint, certainly at the small scale. At a larger scale the pattern of ridges on fingerprints can be categorised as belonging to one of five basic forms: loops (left and right), whorls, arches and tented arches. The population frequencies of these types show little variation with ethnicity and a list of the types occurring on the ten digits can be used as an initial basis for identification of individuals. However, such a system would not uniquely identify an individual although the frequency of certain combinations could be extremely small. At a smaller scale various minutiae or singularities can be observed in a fingerprint. These include ridge endings and bifurcations, amongst others. Typical fingerprints have several hundred of these as well as two key points (with the exception of a simple arch) referred to as the core and delta, which are focal points of the overall pattern of ridges. Modern identification systems are based upon ridge endings and bifurcations, not least because they are the easiest to determine automatically from image analysis. The configuration of these minutiae is unique to the individual. This research explores the relationship between the locations of minutiae to determine if they can be modelled using a statistical process. In addition, since the approach is based on how fingerprints can be examined in a forensic situation an algorithm is created and tested which allows the strength of a match between a fingermark left at a crime and a fingerprint from a known suspect to be calculated. Currently the result of matching a fingermark and fingerprint is expressed as a categorical value of; match, no match or inconclusive. The method in this research allows this to be expressed as a numerical value allowing for a wider and more flexible use of fingerprint evidence

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

Secure and private fingerprint-based authentication

This thesis studies the requirements and processes involved in building an authentication system using the fingerprint biometric, where the fingerprint template is protected during storage and during comparison. The principles developed in this thesis can be easily extended to authentication systems using other biometric modalities. Most existing biometric authentication systems store their template securely using an encryption function. However, in order to perform matching, the enrolled template must be decrypted. It is at this point that the authentication system is most vulnerable as the entire enrolled template is exposed. A biometric is irreplaceable if compromised and can also reveal sensitive information about an individual. If biometric systems are taken up widely, the template could also be used as an individual's digital identifier. Compromise in that case, violates an individual's right to privacy as their transactions in all systems where they used that compromised biometric can be tracked. Therefore securing a biometric template during comparison as well as storage in an authentication system is imperative. Eight different fingerprint template representation techniques, where templates were treated as a set of elements derived from the locations and orientations of fingerprint minutiae, were studied. Four main steps to build any biometric based authentication system were identified and each of the eight fingerprint template representations was inducted through the four steps. Two distinct Error Tolerant Cryptographic Constructs based on the set difference metric, were studied for their ability to securely store and compare each of the template types in an authentication system. The first construct was found to be unsuitable for a fundamental reason that would apply to all the template types considered in the research. The second construct did not have the limitation of the first and three algorithms to build authentication systems using the second construct were proposed. It was determined that minutiae-based templates had significant intra sample variation as a result of which a very relaxed matching threshold had to be set in the authentication system. The relaxed threshold caused the authentication systems built using the first two algorithms to reveal enough information about the stored templates to render them insecure. It was found that in cases of such large intra-sample variation, a commonality based match decision was more appropriate. One solution to building a secure authentication system using minutiae-based templates was demonstrated by the third algorithm which used a two stage matching process involving the second cryptographic construct and a commonality based similarity measure in the two stages respectively. This implementation was successful in securing the fingerprint template during comparison as well as storage, with minimal reduction in accuracy when compared to the matching performance without the cryptographic construct. Another solution is to use an efficient commonality based error tolerant cryptographic construct. This thesis lists the desirable characteristics of such a construct as existence of any is unknown to date. This thesis concludes by presenting good guidelines to evaluate the suitability of different cryptographic constructs to protect biometric templates of other modalities in an authentication system

Mejora de la seguridad y la privacidad de los sistemas biométricos

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones. Fecha de lectura: 02-06-2016This Thesis was printed with the financial support from EPS-UAM and the Biometric Recognition Group-ATVS

CONTACTLESS FINGERPRINT BIOMETRICS: ACQUISITION, PROCESSING, AND PRIVACY PROTECTION

Biometrics is defined by the International Organization for Standardization (ISO) as \u201cthe automated recognition of individuals based on their behavioral and biological characteristics\u201d Examples of distinctive features evaluated by biometrics, called biometric traits, are behavioral characteristics like the signature, gait, voice, and keystroke, and biological characteristics like the fingerprint, face, iris, retina, hand geometry, palmprint, ear, and DNA. The biometric recognition is the process that permits to establish the identity of a person, and can be performed in two modalities: verification, and identification. The verification modality evaluates if the identity declared by an individual corresponds to the acquired biometric data. Differently, in the identification modality, the recognition application has to determine a person's identity by comparing the acquired biometric data with the information related to a set of individuals. Compared with traditional techniques used to establish the identity of a person, biometrics offers a greater confidence level that the authenticated individual is not impersonated by someone else. Traditional techniques, in fact, are based on surrogate representations of the identity, like tokens, smart cards, and passwords, which can easily be stolen or copied with respect to biometric traits. This characteristic permitted a wide diffusion of biometrics in different scenarios, like physical access control, government applications, forensic applications, logical access control to data, networks, and services. Most of the biometric applications, also called biometric systems, require performing the acquisition process in a highly controlled and cooperative manner. In order to obtain good quality biometric samples, the acquisition procedures of these systems need that the users perform deliberate actions, assume determinate poses, and stay still for a time period. Limitations regarding the applicative scenarios can also be present, for example the necessity of specific light and environmental conditions. Examples of biometric technologies that traditionally require constrained acquisitions are based on the face, iris, fingerprint, and hand characteristics. Traditional face recognition systems need that the users take a neutral pose, and stay still for a time period. Moreover, the acquisitions are based on a frontal camera and performed in controlled light conditions. Iris acquisitions are usually performed at a distance of less than 30 cm from the camera, and require that the user assume a defined pose and stay still watching the camera. Moreover they use near infrared illumination techniques, which can be perceived as dangerous for the health. Fingerprint recognition systems and systems based on the hand characteristics require that the users touch the sensor surface applying a proper and uniform pressure. The contact with the sensor is often perceived as unhygienic and/or associated to a police procedure. This kind of constrained acquisition techniques can drastically reduce the usability and social acceptance of biometric technologies, therefore decreasing the number of possible applicative contexts in which biometric systems could be used. In traditional fingerprint recognition systems, the usability and user acceptance are not the only negative aspects of the used acquisition procedures since the contact of the finger with the sensor platen introduces a security lack due to the release of a latent fingerprint on the touched surface, the presence of dirt on the surface of the finger can reduce the accuracy of the recognition process, and different pressures applied to the sensor platen can introduce non-linear distortions and low-contrast regions in the captured samples. Other crucial aspects that influence the social acceptance of biometric systems are associated to the privacy and the risks related to misuses of biometric information acquired, stored and transmitted by the systems. One of the most important perceived risks is related to the fact that the persons consider the acquisition of biometric traits as an exact permanent filing of their activities and behaviors, and the idea that the biometric systems can guarantee recognition accuracy equal to 100\% is very common. Other perceived risks consist in the use of the collected biometric data for malicious purposes, for tracing all the activities of the individuals, or for operating proscription lists. In order to increase the usability and the social acceptance of biometric systems, researchers are studying less-constrained biometric recognition techniques based on different biometric traits, for example, face recognition systems in surveillance applications, iris recognition techniques based on images captured at a great distance and on the move, and contactless technologies based on the fingerprint and hand characteristics. Other recent studies aim to reduce the real and perceived privacy risks, and consequently increase the social acceptance of biometric technologies. In this context, many studies regard methods that perform the identity comparison in the encrypted domain in order to prevent possible thefts and misuses of biometric data. The objective of this thesis is to research approaches able to increase the usability and social acceptance of biometric systems by performing less-constrained and highly accurate biometric recognitions in a privacy compliant manner. In particular, approaches designed for high security contexts are studied in order improve the existing technologies adopted in border controls, investigative, and governmental applications. Approaches based on low cost hardware configurations are also researched with the aim of increasing the number of possible applicative scenarios of biometric systems. The privacy compliancy is considered as a crucial aspect in all the studied applications. Fingerprint is specifically considered in this thesis, since this biometric trait is characterized by high distinctivity and durability, is the most diffused trait in the literature, and is adopted in a wide range of applicative contexts. The studied contactless biometric systems are based on one or more CCD cameras, can use two-dimensional or three-dimensional samples, and include privacy protection methods. The main goal of these systems is to perform accurate and privacy compliant recognitions in less-constrained applicative contexts with respect to traditional fingerprint biometric systems. Other important goals are the use of a wider fingerprint area with respect to traditional techniques, compatibility with the existing databases, usability, social acceptance, and scalability. The main contribution of this thesis consists in the realization of novel biometric systems based on contactless fingerprint acquisitions. In particular, different techniques for every step of the recognition process based on two-dimensional and three-dimensional samples have been researched. Novel techniques for the privacy protection of fingerprint data have also been designed. The studied approaches are multidisciplinary since their design and realization involved optical acquisition systems, multiple view geometry, image processing, pattern recognition, computational intelligence, statistics, and cryptography. The implemented biometric systems and algorithms have been applied to different biometric datasets describing a heterogeneous set of applicative scenarios. Results proved the feasibility of the studied approaches. In particular, the realized contactless biometric systems have been compared with traditional fingerprint recognition systems, obtaining positive results in terms of accuracy, usability, user acceptability, scalability, and security. Moreover, the developed techniques for the privacy protection of fingerprint biometric systems showed satisfactory performances in terms of security, accuracy, speed, and memory usage