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.
Table of Contents
Introduction to the Inverse Problems of Biometrics. Basics of Synthetic Biometric Data Structure Design. Synthetic Signatures. Synthetic Fingerprints. Synthetic Faces. Synthetic Iris. Biometric Data Structure Representation by Voronoi Diagrams. Synthetic DNA. Index.
"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