1st Edition
Biometric Inverse Problems
Traditional methods of biometric analysis are unable to overcome the limitations of existing approaches, mainly due to the lack of standards for input data, privacy concerns involving use and storage of actual biometric data, and unacceptable accuracy. Exploring solutions to inverse problems in biometrics transcends such limits and allows rich analysis of biometric information and systems for improved performance and testing. Although some particular inverse problems appear in the literature, until now there has been no comprehensive reference for these problems.
Biometric Inverse Problems provides the first comprehensive treatment of biometric data synthesis and modeling. This groundbreaking reference comprises eight self-contained chapters that cover the principles of biometric inverse problems; basics of data structure design; new automatic synthetic signature, fingerprint, and iris design; synthetic faces and DNA; and new tools for biometrics based on Voronoi diagrams. Based on the authors' vast experience in the field, the book authoritatively examines new approaches and methodologies in both direct and inverse biometrics, providing invaluable analytical and benchmarking tools. The authors include case studies, examples, and implementation codes for practical illustration of the methods.
Loaded with approximately 200 figures, 60 problems, 50 MATLAB® code fragments, and 200 examples, Biometric Inverse Problems sets the standard for innovation and authority in biometric data synthesis, modeling, and analysis.
Acknowledgements
INTRODUCTION TO THE INVERSE PROBLEMS OF BIOMETRICS
Attacks on Biometric Systems
Classical Direct and Inverse Problems
Direct and Inverse Problems of Biometrics
Basic Notion of Biometric Data
Examples of Synthetic Biometric Data
Conversating of Biometric Information
Design of Biometric Devices and Systems
Applications of Inverse Biometrics
Ethical and Social Aspects of Inverse Biometrics
Summary
Problems
Further Reading
References
BASICS OF SYNTHETIC BIOMETRIC DATA STRUCTURE DESIGN
Basic Concepts of Synthetic Biometric Data Structure Design
Synthesis Strategies
Information Carried by Biometric Data
Generation of Random Biometric Attributes
Degradation Model in Synthesis of Biometric Data
Image Warping
Deformation by Interpolation and Approximation
Extracting and Generating Features
Summary
Problems
Further Reading
References
SYNTHETIC SIGNATURES
Introduction
Basics of Signature Synthesis
Signature Synthesis Techniques
Statistically Meaningful Synthesis
Implementation
Summary
Problems
Further Reading
References
SYNTHETIC FINGERPRINTS
Introduction
Modeling a Fingerprint
Extraction of Features
Library of Topological Primitives
Local Generators: Fingerprint Primitives
Global Generators: Orientation Map
Polar Transformation of Orientation Map
Generating Synthetic Fingerprint Images from an Orientation Map
Other Global Topological Models
Summary
Problems
Further Reading
References
SYNTHETIC FACES
Introduction to Facial Expressions Design
Modeling of Facial Expressions
Facial Topology Transformation and Manipulation
Local Facial Models
Facial Synthesizers
Automated Support of Deceit Detection
Summary
Problems
Further Reading
References
SYNTHETIC IRIS
State-of-the-Art Iris Synthesis
Eye Model
Iris Image Processing
Iris Synthesis by Transformation
Iris Synthesis by Assembling
Summary
Problems
Further Reading
References
BIOMETRIC DATA STRUCTURE REPRESENTATION BY VORONOI DIAGRAMS
Voronoi Data Structure
Basics of Voronoi Diagram Technique
Direct and Inverse Voronoi Transform
Properties
Voronoi Data Structure in Topological Analysis and Synthesis
Topological Compatibility of the Voronoi Diagram
Implementing the Discrete Voronoi Transform with a Distance Transform
Calculating Area Voronoi Diagrams using Nearest-Neighbor Transform
Summary
Problems
Further Reading
References
SYNTHETIC DNA
Introduction
Basics of DNA Biometrics
DNA/Protein Synthesis Techniques
Examples of Markov Models
Postprocessing: Pairwise Alignments
Algorithm for Sequence Generation
Summary
Problems
Further Reading
References
INDEX
Biography
Svetlana N. Yanushkevich, Adrian Stoica, Vlad P. Shmerko, Denis V. Popel, Elizabeth Lynn
"It should be noted that any solution to an inverse problem in any field helps better understand the direct problem and can give more benefits, for example, reconstruction of an object in topography. This book is the first compiled work in this direction … written in a reader-friendly style … the material is well structured and illustrated. In particular, examples are short, clear, and well placed; summaries give the quintessence of each chapter; problems are useful for detail study. I found especially useful the recommendations and comments for further reading provided in each chapter … this book can be recognized as an important event in the biometric community and related areas, including pattern recognition."
-Patrick S. Wang, IAPR (International Association for Pattern Recognition) Newsletter, Vol. 28, No. 4, October 2006