Handbook of Biometrics
by A. K. Jain, P. Flynn, A. A. Ross, (ed.s)
Reviewed by: Lawrence O’Gorman,
Although it is not specifically stated in the book, this appears to be an update of a previous book (Biometrics – Personal Identification in Networked Society, by Jain, Bolle, and Pankanti, Kluwer Press, 1999). Both books contain fundamental material on biometrics. Both contain chapters that are written individually by experts in the field. However, in light of the explosive growth of work in this field, innovations, and new deployments in the last seven years, this recent publication is well warranted.
The chapters in this new book are organized into three sections. The first section has twelve chapters describing different biometric modalities. Can you name all twelve? Here they are: fingerprint, face, iris, hand, gait, ear, voice, palm-print, signature, 3-D face, dental, and vascular. Each chapter describes all or some subset of the following information: the physical nature of the modality, what makes it distinctive, how it is captured, and how it distinguishes itself from other biometrics. Most chapters comprise material that is algorithmic in nature, written by researchers whose main focus is extracting features and matching the particular biometric. Most chapters contain performance evaluation statistics, which cannot be directly compared between modalities (chapters), but which give a basis for understanding how the different biometrics perform relative to one another.
The second section consists of four chapters: introduction to multi-biometrics, multi-spectral face recognition, face and ear, and ancillary information. Both the introduction to multi-biometrics and the ancillary information chapters deal with the issue of how to combine multiple pieces of information most effectively for matching – a process called fusion. “Ancillary information” refers to the extra information that might accompany a biometric such as the weight or height of the person (termed “soft biometrics” in the book). The paper on ear and face describes both modalities in isolation and the result of fusion of these two. The multi-spectral face recognition chapter does not deal with multiple biometrics, but rather multiple image capture modalities, which include visible and infrared light image reflectance.
The third section consists of eight chapters dealing with: law, system security, spoofing, forensic science, government use, commercial use, standards, and databases. I found this eclectic section to be particularly interesting. Just to focus on one of these chapters, the one describing linkages between biometrics and forensics discusses the law enforcement side of biometrics, its history, and how new developments are also used for forensics. This chapter traces from the beginnings of forensic biometrics, the field of anthropometry as pioneered by the French ethnologist Bertillon. It describes AFIS (Automatic Fingerprint Identification Systems) that began computer biometrics in the late 1960s, the more recent revolution in the use of DNA for forensics, and also includes handwriting, voice, face, ear, and dental.
A researcher, practitioner, or student in the field of biometrics will want to have at least one fundamental book in this field. This book is an excellent choice. However, one should note that there are two types of fundamental texts. One is this edited text, where each chapter is written by different authors. The other is a text written in full by one or more authors – call this a traditional academic text. An advantage of the edited text is that authors of each chapter are most familiar with their topic and can offer particular insights gained from working in depth in that area. An advantage of a traditional academic text is that it can have a more cohesive and consistent presentation. Of course there are overlaps between the two because editors encourage chapter authors to follow a consistent style, and an academic text is written by experts as well. An example of a biometric book that follows the format of a traditional academic text is, Guide to Biometrics by Bolle et al. (reviewed Jan ’05 issue of the IAPR Newsletter).
Handbook of Biometrics provides a valuable addition to the biometrics section of my own bookcase. I anticipate that I will consult it frequently as I did the previous Jain text.
As a postscript, I received another biometrics book published concurrently to the book reviewed above. The book, Advances in Biometrics – Sensors, Algorithms, and Systems, edited by Ratha and Govindaraju also contains chapters written by various experts, but its stated purpose is different: it focuses on advances rather than covering mainly the fundamentals of the field. I found these two books to be complementary. See the review of this book in this issue.
Click above to go to the publisher’s web page where you can read about this book and link to the Table of Contents.
Book Reviews Published in
the IAPR Newsletter
Practical Algorithms for Image Analysis, 2 ed.
by O’Gorman, Sammon and Seul
The Dissimilarity Representation for Pattern Recognition: Foundations and Applications
by Pekalska and Duin
Advances in Biometrics –
Sensors, Algorithms, and Systems
by Ratha and Govindaraju, (Editors)
Dynamic Vision for Perception and Control of Motion
by Polanski and Kimmel
Introduction to clustering large and high-dimensional data
The Text Mining Handbook
by Feldman and Sanger
Information Theory, Inference,
and Learning Algorithms
“Foundations and Trends in Computer Graphics and Vision”
Curless, Van Gool, and Szeliski., Editors
Applied Combinatorics on Words
by M. Lothaire
Human Identification Based on Gait
by Nixon, Tan and Chellappar
Mathematics of Digital Images
by Stuart Hogan
Advances in Image and Video Segmentation
Graph-Theoretic Techniques for Web Content Mining
by Schenker, Bunke, Last and Kandel
Handbook of Mathematical Models in Computer Vision
by Paragios, Chen, and Faugeras (Editors)
The Geometry of Information Retrieval
by van Rijsbergen
Biometric Inverse Problems
by Yanushkevich, Stoica, Shmerko and Popel
Correlation Pattern Recognition
by Kumar, Mahalanobis, and Juday
Pattern Recognition 3rd Edition
by Theodoridis and Koutroumbas
Dictionary of Computer Vision and
by R.B. Fisher, et. Al
Kernel Methods for Pattern Analysis
by Shawe-Taylor and Cristianini
Machine Vision Books
CVonline: an overview
The Guide to Biometrics by Bolle, et al
Pattern Recognition Books
Jul. ‘04 [pdf]