Fractal analysis of fingerprints

Current methods for comparing fingerprints have weaknesses that have opened them to criticism. Current methods concentrate on the comparison of minutia in the print either manually or with the assistance of a computer algorithm. This causes these methods to depend highly on the presence of minutia and their relationship to one another. Absence or rotations of minutia can prevent current methods form making accurate comparisons. The goal of this process is to develop a new method for analyzing fingerprints that addresses many of the concerns with current methods.;The developed process uses an iterated function sequence (IFS) to convert the image of a fingerprint into a fractal pattern. The input for the IFS is constructed by a random walk through the image. Once a fingerprint is converted into a fractal pattern, the fractals can be used to make comparisons. Fractals are well defined mathematical objects that make them far easier to compare than fingerprints themselves. This process addresses many of the issues with current methods. This method is global in nature and thus it is not dependent on a set number of minutiae. Moreover, the rules for the random walk are constructed so as to make the fractal produced invariant of orientation of the print.;This method offers a new fast way to compare images. This method can be used to increase confidence, both in court and public opinion, in the use of fingerprints as identification. It can offer both an independent and/or supplemental method to the current ones used

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

Fingerprint Recognition: A Histogram Analysis Based Fuzzy C-Means Multilevel Structural Approach

In order to fight identity fraud, the use of a reliable personal identifier has become a necessity. Fingerprints are considered one of the best biometric measurements and are used as a universal personal identifier. There are two main phases in the recognition of personal identity using fingerprints: 1) extraction of suitable features of fingerprints, and 2) fingerprint matching making use of the extracted features to find the correspondence and similarity between the fingerprint images. Use of global features in minutia-based fingerprint recognition schemes enhances their recognition capability but at the expense of a substantially increased complexity. The recognition accuracies of most of the fingerprint recognition schemes, which rely on some sort of crisp clustering of the fingerprint features, are adversely affected due to the problems associated with the behavioral and anatomical characteristics of the fingerprints. The objective of this research is to develop efficient and cost-effective techniques for fingerprint recognition, that can meet the challenges arising from using both the local and global features of the fingerprints as well as effectively deal with the problems resulting from the crisp clustering of the fingerprint features. To this end, the structural information of local and global features of fingerprints are used for their decomposition, representation and matching in a multilevel hierarchical framework. The problems associated with the crisp clustering of the fingerprint features are addressed by incorporating the ideas of fuzzy logic in developing the various stages of the proposed fingerprint recognition scheme. In the first part of this thesis, a novel low-complexity multilevel structural scheme for fingerprint recognition (MSFR) is proposed by first decomposing fingerprint images into regions based on crisp partitioning of some global features of the fingerprints. Then, multilevel feature vectors representing the structural information of the fingerprints are formulated by employing both the global and local features, and a fast multilevel matching algorithm using this representation is devised. Inspired by the ability of fuzzy-based clustering techniques in dealing more effectively with the natural patterns, in the second part of the thesis, a new fuzzy based clustering technique that can deal with the partitioning problem of the fingerprint having the behavioral and anatomical characteristics is proposed and then used to develop a fuzzy based multilevel structural fingerprint recognition scheme. First, a histogram analysis fuzzy c-means (HA-FCM) clustering technique is devised for the partitioning of the fingerprints. The parameters of this partitioning technique, i.e., the number of clusters and the set of initial cluster centers, are determined in an automated manner by employing the histogram of the fingerprint orientation field. The development of the HA-FCM partitioning scheme is further pursued to devise an enhanced HA-FCM (EAH-FCM) algorithm. In this algorithm, the smoothness of the fingerprint partitioning is improved through a regularization of the fingerprint orientation field, and the computational complexity is reduced by decreasing the number of operations and by increasing the convergence rate of the underlying iterative process of the HA-FCM technique. Finally, a new fuzzy based fingerprint recognition scheme (FMSFR), based on the EHA-FCM partitioning scheme and the basic ideas used in the development of the MSFR scheme, is proposed. Extensive experiments are conducted throughout this thesis using a number of challenging benchmark databases. These databases are selected from the FVC2002, FVC2004 and FVC2006 competitions containing a wide variety of challenges for fingerprint recognition. Simulation results demonstrate not only the effectiveness of the proposed techniques and schemes but also their superiority over some of the state-of-the-art techniques, in terms of the recognition accuracy and the computational complexity

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