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Introduction to Biometrics

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TLDR
This tutorial is to introduce the fundamentals of biometric technology from a pattern recognition and signal processing perspective by discussing some of the prominent techniques used in the field and to convey the recent advances made in this field especially in the context of security, privacy and forensics.
Abstract
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 ones 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.

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Citations
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Journal ArticleDOI

Recent advances in the automatic recognition of audiovisual speech

TL;DR: The main components of audiovisual automatic speech recognition (ASR) are reviewed and novel contributions in two main areas are presented: first, the visual front-end design, based on a cascade of linear image transforms of an appropriate video region of interest, and subsequently, audiovISual speech integration.
Journal ArticleDOI

50 years of biometric research

TL;DR: Unlocking the full potential of biometrics through inter-disciplinary research in the above areas will not only lead to widespread adoption of this promising technology, but will also result in wider user acceptance and societal impact.
Journal ArticleDOI

Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition

TL;DR: A novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts and the experimental results show that the proposed method is highly competitive compared with other state-of-the-art approaches.
Proceedings ArticleDOI

Live face detection based on the analysis of Fourier spectra

TL;DR: In this article, an effective live face detection algorithm is presented based on the analysis of Fourier spectra of a single face image or face image sequences using structure and movement information of live face.

Audio-Visual Automatic Speech Recognition: An Overview

TL;DR: Novel, non-traditional approaches, that use orthogonal sources of information to the acoustic input, are needed to achieve ASR performance closer to the human speech perception level, and robust enough to be deployable in field applications.
References
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Journal ArticleDOI

Eigenfaces for recognition

TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Journal ArticleDOI

An introduction to biometric recognition

TL;DR: A brief overview of the field of biometrics is given and some of its advantages, disadvantages, strengths, limitations, and related privacy concerns are summarized.
Book

Handbook of Fingerprint Recognition

TL;DR: This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.
Journal ArticleDOI

High confidence visual recognition of persons by a test of statistical independence

TL;DR: A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence, which implies a theoretical "cross-over" error rate of one in 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates.
Journal ArticleDOI

How iris recognition works

TL;DR: Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests.
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