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Über dieses Buch

Biometric recognition, or simply biometrics, is the science of establishing the identity of a person based on physical or behavioral attributes. It is a rapidly evolving field with applications ranging from securely accessing one’s computer to gaining entry into a country. While the deployment of large-scale biometric systems in both commercial and government applications has increased the public awareness of this technology, "Introduction to Biometrics" is the first textbook to introduce the fundamentals of Biometrics to undergraduate/graduate students. The three commonly used modalities in the biometrics field, namely, fingerprint, face, and iris are covered in detail in this book. Few other modalities like hand geometry, ear, and gait are also discussed briefly along with advanced topics such as multibiometric systems and security of biometric systems. Exercises for each chapter will be available on the book website to help students gain a better understanding of the topics and obtain practical experience in designing computer programs for biometric applications. These can be found at: http://www.csee.wvu.edu/~ross/BiometricsTextBook/.

Designed for undergraduate and graduate students in computer science and electrical engineering, "Introduction to Biometrics" is also suitable for researchers and biometric and computer security professionals.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract
The ability to identify individuals uniquely and to associate personal attributes (e.g., name, nationality, etc.) with an individual has been crucial to the fabric of human society. Humans typically use body characteristics such as face, voice, and gait along with other contextual information (e.g., location and clothing) to recognize one another. The set of attributes associated with a person constitutes their personal identity. In the early days of civilization, people lived in small communities where individuals could easily recognize each other. However, an explosion in population growth accompanied by increased mobility in modern society has necessitated the development of sophisticated identity management systems that can efficiently record, maintain, and obliterate personal identities of individuals.
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Chapter 2. Fingerprint Recognition

Abstract
Unlike the skin on most parts of our body, which is smooth and contains hair and oil glands, the skin on the palms and soles exhibits a flow-like pattern of ridges and valleys (sometimes referred to as furrows), and contains no hair or oil glands. These papillary ridges on the finger, called friction ridges, help the hand to grasp objects by increasing friction and improving the tactile sensing of surface textures. The friction ridge skin is composed of two major layers: dermis (inner layer) and epidermis (outer layer).
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Chapter 3. Face Recognition

Abstract
The face is the frontal portion of the human head, extending from the forehead to the chin and includes the mouth, nose, cheeks, and eyes. Being the foremost part in one’s interactions with the outer world, the face houses most of the fundamental sensory organs necessary for perceiving the world around, namely, eyes for seeing, nose for smelling, mouth for tasting, and ears for hearing. The face is considered to be the most commonly used biometric trait by humans; we recognize each other and, in many cases, establish our identities based on faces. Hence, it has become a standard practice to incorporate face photographs in various tokens of authentication such as ID cards, passports, and driver’s licenses.
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Chapter 4. Iris Recognition

Abstract
The use of the ocular region as a biometric trait has gained impetus, especially due to significant advancements made in iris recognition since 1993. The ocular region of the human face consists of the eyes and the surrounding structures such as facial skin, eyebrows, and nose bridge (Figure 4.1). While various components of the eye have been proposed as biometric indicators (viz., iris, retina, and conjunctival vasculature), it is the iris that has been extensively studied in the biometrics literature and used in large-scale biometric systems.
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Chapter 5. Additional Biometric Traits

Abstract
As stated in Chapter 1, a wide variety of biometric traits have been proposed and studied in the literature. In some cases, academic curiosity about the uniqueness and permanence of certain biological traits has spurred exploratory research (e.g., iris); in other cases, new application domains have resulted in the exploration of novel biometric traits (e.g., periocular biometrics). Furthermore, certain biometric traits are uniquely suited for some applications and scenarios.
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Chapter 6. Multibiometrics

Abstract
Person recognition systems based on individual biometric traits like fingerprint, face, and iris have been the focus of this book thus far. Most of these biometric systems can be labeled as unibiometric systems because they rely on a single biometric source for recognition. Any piece of evidence that can be independently used to recognize a person is called a source of biometric information. Unibiometric systems have some limitations.What if the biometric source becomes unreliable due to sensor or software malfunction, poor quality of specific biometric trait of the user, or deliberate manipulation? Furthermore, high-security applications and large-scale civilian identification systems place stringent accuracy requirements that cannot be met by existing unibiometric systems.
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Chapter 7. Security Of Biometric Systems

Abstract
A natural question that arises in biometric recognition is which biometric system is “best” suited for a particular application. Of course, the answer to this question depends not only on technical merits and limitations of the biometric system (e.g., matching accuracy and throughput), but also on other socio-economic factors like user acceptability and system cost. However, given that all other factors are equal, one would obviously prefer a biometric system that has the least probability of failure.
Anil K. Jain, Arun A. Ross, Karthik Nandakumar

Backmatter

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