Biometrics Books

This volume was edited by two world renown statisticians who have made major contributions to Biometry. It is a collection of 21 articles surveying statistical methods that were developed over the past 50 year and have had an impact on the science of biology (biometrics). The volume was proposed by Lynn Billard in 1996 to celebrate the 50th aniverary of the International Biometrics Society (IBS)and their journal Biometrics. Interesting accounts of the history of the society and the journal can be found in the first paper by Billard (then the President of the IBS)and the second paper by James. The third paper by Bradley and Anderson deals with an historical account of the contributions of the society and the journal to experimental design. Dagnelie provides an historical account of the teaching of biometry. The remaining papers are more technical and deal with special topics, all written by experts. Searle and McCulloch discuss the developments over the 50 year period 1945 to 1995 in linear models. Imrey, Koch and Preisser look at categorical data modeling. C. R. Rao talks about Hierarchical Bayesian procedures. Efron and Tibshirani discuss computer-intensive methods. Gower discusses multivariate analysis and multidimensional scaling. Anderson and Keiding cover survival analysis. Nelder covers statistical computing advances and the use of computer-intensive methods, graphics, computer algebra and expert systems and their impact on biostatistics. Patil covers ecology and environmental methods. Freeman and Riley discuss agriculture and forestry. Thomson deal with the latest hot topic - genetics. Breslow covers epidemiology and Dietz talks about infectious disease epidemology. Ware and Liang cover another important topic - longitudal studies. Diggle covers spatial data analysis. Glasbey and Berman review image analysis. The articles are well written and scholarly and most are great reference articles for historical developments up to 1996. This is a rapidly evolving and important field. Many statistician including me, have moved into biostatistics from other fields and now work in the medical device or pharmaceutical industry. To us, this in an invaluable reference source.
The field has continued to advance over the past 4 years. Still this book establishes a foundation and provides an historical perspective to the methods that we current use and continue to research.

This volume was edited by two world renown statisticians who have made major contributions to Biometry. It is a collection of 21 articles surveying statistical methods that were developed over the past 50 year and have had an impact on the science of biology (biometrics). The volume was proposed by Lynn Billard in 1996 to celebrate the 50th aniverary of the International Biometrics Society (IBS)and their journal Biometrics. Interesting accounts of the history of the society and the journal can be found in the first paper by Billard (then the President of the IBS)and the second paper by James. The third paper by Bradley and Anderson deals with an historical account of the contributions of the society and the journal to experimental design. Dagnelie provides an historical account of the teaching of biometry. The remaining papers are more technical and deal with special topics, all written by experts. Searle and McCulloch discuss the developments over the 50 year period 1945 to 1995 in linear models. Imrey, Koch and Preisser look at categorical data modeling. C. R. Rao talks about Hierarchical Bayesian procedures. Efron and Tibshirani discuss computer-intensive methods. Gower discusses multivariate analysis and multidimensional scaling. Anderson and Keiding cover survival analysis. Nelder covers statistical computing advances and the use of computer-intensive methods, graphics, computer algebra and expert systems and their impact on biostatistics. Patil covers ecology and environmental methods. Freeman and Riley discuss agriculture and forestry. Thomson deal with the latest hot topic - genetics. Breslow covers epidemiology and Dietz talks about infectious disease epidemology. Ware and Liang cover another important topic - longitudal studies. Diggle covers spatial data analysis. Glasbey and Berman review image analysis. The articles are well written and scholarly and most are great reference articles for historical developments up to 1996. This is a rapidly evolving and important field. Many statistician including me, have moved into biostatistics from other fields and now work in the medical device or pharmaceutical industry. To us, this in an invaluable reference source.

The field has continued to advance over the past 4 years. Still this book establishes a foundation and provides an historical perspective to the methods that we current use and continue to research.

The book has a compelling usage. How can we use statistics to find advance warning of terrorists and their intents? The book does have fascinating examples of data mining techniques. The problem is that with only one exception, they are highly speculative. Few of these can give a definitive indicator. Very subjective. The efficacy might be questioned.

The exception is where the book deals with biometrics. Here, there is within reason, an objective test of whether a person passes a biometric test or not. In other words, is a person indeed this person whose biometric data has been earlier recorded. This has use, in cases where we might validate that a person has been prescreened, and can thus now perhaps bypass some current tests. The problem in the context of terrorism, is when a terrorist has not been diagnosed as such. Then all the biometric tests can do is say that a person has a valid id, for example. Given this, terrorist groups can be expected to recruit new people and sleepers, in part to nullify any biometric tests.

The book is a commendable effort to tackle a dangerous and ongoing problem. But readers should be cautioned not to put too much store in its methods.

After the 9/11 terrorist attack using commercial airplanes to crash into the pentagon and the world trade center buildings, statisticians among other found their way into developing tools to deal with the such problems. This book is an edited volume of of statistical researchers effort at solving some specific problems addressing potential terrorist attacks and finding ways to prevent future occurrences. Of the topics included are 1. game theory and risk taking, 2. biometric authentication (a pattern recognition technique for matching signatures, 3. matching faces for identification of terriorists using fake identification, 4. and DNA among other things.

Many well known statisticians from RAND, the Naval Postgraduate School, the National Institute of Science and Technology, Los Alamos National Laboratory and some academic institutions present papers on a variety of topics including game theory, biometric authentification, aggregated algorithms, syndromic surveillance, pattern recognition, simulation studies and other counterterrorism approaches.

This book is the first of its kind and it really shows how statistics can play a major role as analytic tools for counterterrorism.

Affective Computing and Intelligent Interaction: First International Conference - if you want to know recent researches in this field you have to buy this book!

Target Audience:

Business and management types who are tasked with implementing a Biometrics solution when they know nothing about Biometrics. This is a good overview for non-technical users.

Summary:

This is an easy read that will get you oriented into the world of Biometrics. For a technical person, the book will almost be boring at times, but give it a chance and you may learn a little bit. If you already know a bit jump to Chapter 12 and explore "Ten Tools Used in Biometrics" From there you can jump back to Part Two (Chapter 4) and explore Biometric systems in more depth.

Chapter 3 discusses Biometrics, law and society. On page 56 I was reminded why Biometrics is less of a problem in the EU. They have tougher privacy laws. The very accurate observation here was that Europeans are much more secure with Biometrics because they are much more protected. I can personally vouch for that. Been there, seen that.

The only real disappointment of this book is that they didn't touch more on RFID and Biometrics. It may have been beyond the scope of the book. That wouldn't stop me from buying it though. The list price is $29.99 US, but I can see that Amazon has it for much less, which makes it more attractive.

I have not compared this against other books on the subject. There may be better out there. What you get out of this is based on criteria, but again if you just getting started and are non-technical, this an easy start.

This book is a general textbook on biometric fundamentals as opposed to discussions on specific biometric measurements - fingerprint, iris, face recognition etc. Rather than just chatter on endlessly like an academic journal, the author keeps things interesting with numerical insights and practical suggestions. The book is divided into four parts.

Part one serves as an introduction and is only sixty pages long. Chapters 1 and 2 acquaint the reader with biometric terminology. For example, the authors explain the difference between verification, identification, screening, and continuity of identity systems. They also explain how biometric matching is fundamentally different from password matching in computer security. You can make a password so complex and long that it is very difficult to crack - and difficult to use. Alternatively, the strength of a biometric system is limited by the information content of the biometric characteristic - you cannot make it arbitrarily more complex. Nature limits you. In Chapters 3 and 4, the basic concepts are introduced underlying common biometric systems such as fingerprint, face, speaker, iris, hand geometry, and signature recognition systems. Emerging biometric systems such as those that use DNA, retina, thermograms, gait, keystroke, ear, skin reflectance, lip motion, and body odor for recognition are also mentioned. This is all a very brief and shallow treatment.

Part two talks about the mathematics needed to perform biometric matching. The various system errors that can occur are addressed in chapters 5 and 6. Chapter 6 enhances the reader's understanding of biometric identification, which is a much harder problem than verification. Chapter 7 points out that the best strategy to evaluate biometric systems is to organize competitions among biometric systems and conduct comparative evaluations on a common database and testing protocol. In Chapter 8, the authors provide guidelines on how to select a suitable biometric for various applications. The advantages and disadvantages of each biometric technology is discussed and some of the prevalent myths are debunked.

Part three deals with system issues associated with implementing biometric systems. Chapter 9 discusses enrollment issues when creating and maintaining a database. Many system level issues arise when the database size is very large. In case of certain biometric applications, such as national identification card or driver's license, the database could contain tens of millions of identities and hundreds of millions of biometric samples. In Chapter 10, the authors walk the readers through large-scale system issues. Decision and score level fusions are discussed in Chapter 11 for verification and identification systems. Common design techniques used to secure biometric systems are discussed in Chapter 12, and standards for APIs and databases, certifications and legislation are the topics of Chapter 13.

Part four covers advanced topics. In Chapter 14, the authors present how to estimate the individuality in iris and fingerprint biometrics. Chapter 15 deals with system errors and confidence intervals. In Chapter 16, the authors discuss how cost functions can be used to choose the operating point of a matcher. Finally, methods of estimating the cumulative match curve in identification systems and its relation to the false accept/reject rates are discussed. Chapter 17 is entirely about future trends in biometrics. Since this book was written in 2003, in many cases, the future is now and these trends are already being or have been implemented at least in part.

This book could have been better if some exercises had been included with each chapter. Particularly with all of the statistics and database theory floating around in this book, more practical examples and exercises would enhance student confidence in these areas. However, it is still a good book on the fundamentals of biometrics and the considerations that go into designing a system regardless of the biometric(s) chosen.

The problem tackled by this book is buried deep in evolution. It is one of the most basic properties of an organism that it reliably recognise others of its species. For reproduction, if nothing else. Humans have the added twist that facial recognition is important, for the extra reasons that the face is usually hairless and has many expressive muscles.

But the way the mind does its analysis is still largely opaque. By contrast, most of the book's methods look at it via other approaches. Signal processing with many custom features specific to faces. The chapters show impressive current capabilities. However, they also readily indicate the limitations. And suggest possible future improvements.

This is a very nice reference book for fingerprint and face recognition. It consists of six chapters each in these two topics. The first chapters are reserved for introduction to the problems, discussion of the important issues and an extensive survey of the literature. In the following chapters, latest techniques are presented for solving problems such as enhancement, segmentation, feature extraction, representation and classification. An invaluable resource for starters to get a quick view of the lietrature and learn about the latest developments.

This book has 6 chapters on fingerprinting and 7 on face identification. The 3 overview chapters are informative and somewhat useful. There are lots of references in the book. Many of the other chapters are long descriptions of new, unproven ideas with much detail and little evaluation or motivation

In light of the circumstances following 9-11, this book sheds light on the technological direction that biometrics will provide in identifying the populous.

While these thoughts may send thoughts of "Orwell" in the minds of many readers, the benefits to be gained by utilizing biometric technology will clearly eliminate a substantial amount of fraud and identity theft within our society,

While this book is technocal in nature, it is written in a non-technocal format and focuses much of the attention on the application aspect of the technology. This is a great read for the businessman seeking new venues to employ technical advances into the business process.

This book is a very good practical guide for all those wishing to actually implement biometric systems. It cuts right through to the practical issues and doesn't get lost in unnecessary technical detail. The example project section is especially valuable and gives a great deal of useful and practical information which is not available in purely academic works. For anyone actually designing or using biometric systems, this book is worth its weight in gold

This is the best overall book on the subject of biometrics for potential users - bar none. For anyone who is interested in actually implenting a biometric system, then this book is essential reading as it covers much more than just the technology and offers much practical insight. The introductory sections make a particularly interesting read and I found the whole book extremely thought provoking and enjoyable from cover to cover. Excellent!

This book was disappointing. The presentation of biometrics was very shallow. I wanted to learn more detailed information about biometrics but the treatment in this book was very superficial.

This is only an introductory book in biometrics. It doesn't explains neither algorithms nor techniques, only shows some facts of biometrics. I don't recommend this book.

Many chapters ramble on with insignificant facts making it difficult to see what point the author is trying to make. Typographical errors are abundant due to insufficient editing and proofreading. I recommend schools find a different text to ethics in technology courses.

Excellent chapters covering morality, law, ethics, professional codes, and intellectual property rights. Provides a basic introduction to many topics that stimulate further study, research, and discussion. Discussion of social issues is limited. The weaker chapters are the modern areas of the information age such as cyberspace, the internet, email, privacy, security, artificial intelligence, and virtual reality.

Any time you can pick up a used copy of a recently published technical book on an interesting topic at one-fourth of the retail price, you know there must be a problem. You would be right. This book tries to do three things at the same time and fails with at least two of its goals. It tries to talk about the business issues of biometrics, technical issues of specific biometric technologies (face recognition, speech recogniton, etc.), and finally machine learning techniques used to accomplish the biometric measurements. Only at this last goal do I think the book comes close to success, and even then only on a sketchy high level. The first seven chapters do an OK job of explaining machine learning techniques and give you some very instructive figures that are often lacking in academic textbooks, especially on neural networks. Also, these chapters do a pretty good job of explaining the equations involved. What's lacking, though, even in these early chapters, are some simple numerical examples or algorithmic steps that would give you some guidance on how to approach a task. When the book tries to make the leap to connecting the machine learning techniques to biometric authentication in a meaningful way such that a computer scientist could code up an algorithm, the book really falls on its face. There are some nice block diagrams of biometric systems, but no real details on algorithmic steps that would allow you to realize any of those blocks. Instead, there is quite a bit of verbage on the competition involved on building particular kinds of systems, and some rhetoric on possible pitfalls in specific biometric designs. However, with you standing there not knowing where to start with your design, this advice is really not very helpful.

I would say pass on this book and if you need to learn machine learning techniques, start with the older book by Mitchell entitled "Machine Learning". It talks about all of the machine learning techniques mentioned in this book, plus there are plenty of examples. Used copies are still relatively inexpensive, and its content is accessible and complete. As for biometric techniques, I've found the best books concentrate on one technique, such as fingerprint verification, and don't stray into other forms of authentication. The following is the table of contents:

Chapter 1. Overview
Chapter 2. Biometric Authentication Systems
Chapter 3. Expectation-Maximization Theory
Chapter 4. Support Vector Machines
Chapter 5. Multi-Layer Neural Networks
Chapter 6. Modular and Hierarchical Networks
Chapter 7. Decision-Based Neural Networks
Chapter 8. Biometric Authentication by Face Recognition
Chapter 9. Biometric Authentication by Voice Recognition
Chapter 10. Multicue Data Fusion
Appendix A: Convergence Properties of EM
Appendix B: Average Det Curves
Appendix C: Matlab Projects