Biometrics-based authentication and identification are emerging as the most reliable method to authenticate and identify individuals. Biometrics requires that the person to be identified be physically present at the point-of-identification and relies on `something which you are or you do' to provide better security, increased efficiency, and improved accuracy. Automated biometrics deals with physiological or behavioral characteristics such as fingerprints, signature, palmprint, iris, hand, voice and face that can be used to authenticate a person's identity or establish an identity from a database. With rapid progress in electronic and Internet commerce, there is also a growing need to authenticate the identity of a person for secure transaction processing. Designing an automated biometrics system to handle large population identification, accuracy and reliability of authentication are challenging tasks. Currently, there are over ten different biometrics systems that are either widely used or under development. Some automated biometrics, such as fingerprint identification and speaker verification, have received considerable attention over the past 25 years, and some issues like face recognition and iris-based authentication have been studied extensively resulting in successful development of biometrics systems in commercial applications. However, very few books are exclusively devoted to such issues of automated biometrics. Automated Biometrics: Technologies and Systems systematically introduces the technologies and systems, and explores how to design the corresponding systems with in-depth discussion. The issues addressed in this book are highly relevant to many fundamental concerns of both researchers and practitioners of automated biometrics in computer and system security.

An easy-to-understand synopsis of identification systems, presenting in simple language the process of fingerprint identification, from the initial capture of a set of finger images, to the production of a Rapsheet. No other single work exists which reviews this important identification process from beginning to end. We examine the identification process for latent (crime scene) prints and how they are identified with these systems. While the primary focus is automated fingerprint identifications, the book also touches on the emergence and use of fingerprints in other biometric systems.Criminal justice administrators, policy makers, and students of forensic science and criminal justice will find a reference to the known limitations and advantages of these systems.This book provides information as to the critical and continual need for properly trained individuals as well as an understanding of the direct and indirect costs associated with maintaining these systems. An understanding of the entire system and what it means will prove invaluable. Why are there missed identifications? Why are identifications made on one database that are not made on another database? Key terms and issues are included, and well as suggestions for improving the overall number of identifications.The book will go beyond process and also discuss issues such as interoperability, management strategies for large databases, contract development, lights out verification and several other issues which impact automated identifications.- The first comprehensive title on this subject area- Outlines in detail the entire process of fingerprint gathering and identity verification - The future of AFIS will is discussed, including national standards in developing multi-agency cooperation/interoperability (U.S.) in addition to the use of AFIS identification world-wide.

An authoritative survey of intelligent fingerprint-recognition concepts, technology, and systems is given. Editors and contributors are the leading researchers and applied R&D developers of this personal identification (biometric security) topic and technology. Biometrics and pattern recognition researchers and professionals will find the book an indispensable resource for current knowledge and technology in the field.

Biometric Systems provides practitioners with an overview of the principles and methods needed to build reliable biometric systems. It covers three main topics: key biometric technologies, design and management issues, and the performance evaluation of biometric systems for personal verification/identification. The four most widely used technologies are focused on - speech, fingerprint, iris and face recognition. Key features include: in-depth coverage of the technical and practical obstacles which are often neglected by application developers and system integrators and which result in shortfalls between expected and actual performance; and protocols and benchmarks which will allow developers to compare performance and track system improvements.

Since the 1960s, a significant effort has been underway to program computers to “see” the human face—to develop automated systems for identifying faces and distinguishing them from one another—commonly known as Facial Recognition Technology. While computer scientists are developing FRT in order to design more intelligent and interactive machines, businesses and states agencies view the technology as uniquely suited for “smart” surveillance—systems that automate the labor of monitoring in order to increase their efficacy and spread their reach. Tracking this technological pursuit, Our Biometric Future identifies FRT as a prime example of the failed technocratic approach to governance, where new technologies are pursued as shortsighted solutions to complex social problems. Culling news stories, press releases, policy statements, PR kits and other materials, Kelly Gates provides evidence that, instead of providing more security for more people, the pursuit of FRT is being driven by the priorities of corporations, law enforcement and state security agencies, all convinced of the technology’s necessity and unhindered by its complicated and potentially destructive social consequences. By focusing on the politics of developing and deploying these technologies, Our Biometric Future argues not for the inevitability of a particular technological future, but for its profound contingency and contestability.

Biometric recognition-the automated recognition of individuals based on their behavioral and biological characteristic-is promoted as a way to help identify terrorists, provide better control of access to physical facilities and financial accounts, and increase the efficiency of access to services and their utilization. Biometric recognition has been applied to identification of criminals, patient tracking in medical informatics, and the personalization of social services, among other things. In spite of substantial effort, however, there remain unresolved questions about the effectiveness and management of systems for biometric recognition, as well as the appropriateness and societal impact of their use. Moreover, the general public has been exposed to biometrics largely as high-technology gadgets in spy thrillers or as fear-instilling instruments of state or corporate surveillance in speculative fiction. Now, as biometric technologies appear poised for broader use, increased concerns about national security and the tracking of individuals as they cross borders have caused passports, visas, and border-crossing records to be linked to biometric data. A focus on fighting insurgencies and terrorism has led to the military deployment of biometric tools to enable recognition of individuals as friend or foe. Commercially, finger-imaging sensors, whose cost and physical size have been reduced, now appear on many laptop personal computers, handheld devices, mobile phones, and other consumer devices. Biometric Recognition: Challenges and Opportunities addresses the issues surrounding broader implementation of this technology, making two main points: first, biometric recognition systems are incredibly complex, and need to be addressed as such. Second, biometric recognition is an inherently probabilistic endeavor. Consequently, even when the technology and the system in which it is embedded are behaving as designed, there is inevitable uncertainty and risk of error. This book elaborates on these themes in detail to provide policy makers, developers, and researchers a comprehensive assessment of biometric recognition that examines current capabilities, future possibilities, and the role of government in technology and system development.

Automated facial recognition algorithms are increasingly intervening in society. This book offers a unique analysis of these algorithms from a critical visual culture studies perspective. The first part of this study examines the example of an early facial recognition algorithm called »eigenface« and traces a history of the merging of statistics and vision. The second part addresses contemporary artistic engagements with facial recognition technology in the work of Thomas Ruff, Zach Blas, and Trevor Paglen. This book argues that we must take a closer look at the technology of automated facial recognition and claims that its forms of representation are embedded with visual politics. Even more significantly, this technology is redefining what it means to see and be seen in the contemporary world.

Biometrics: Personal Identification in Networked Society is a comprehensive and accessible source of state-of-the-art information on all existing and emerging biometrics: the science of automatically identifying individuals based on their physiological or behavior characteristics. In particular, the book covers: *General principles and ideas of designing biometric-based systems and their underlying tradeoffs *Identification of important issues in the evaluation of biometrics-based systems *Integration of biometric cues, and the integration of biometrics with other existing technologies *Assessment of the capabilities and limitations of different biometrics *The comprehensive examination of biometric methods in commercial use and in research development *Exploration of some of the numerous privacy and security implications of biometrics. Also included are chapters on face and eye identification, speaker recognition, networking, and other timely technology-related issues. All chapters are written by leading internationally recognized experts from academia and industry. Biometrics: Personal Identification in Networked Society is an invaluable work for scientists, engineers, application developers, systems integrators, and others working in biometrics.

The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)

Recent advances in biometrics include new developments in sensors, modalities and algorithms. As new sensors are designed, newer challenges emerge in the algorithms for accurate recognition. Written for researchers, advanced students and practitioners to use as a handbook, this volume captures the very latest state-of-the-art research contributions from leading international researchers. It offers coverage of the entire gamut of topics in the field, including sensors, data acquisition, pattern-matching algorithms, and issues that impact at the system level, such as standards, security, networks, and databases