Biometric Inverse Problems

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ISBN: 9780849328992 | 0849328993
Cover: Hardcover
Copyright: 5/5/2005

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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.

Preface

xiii

Acknowledgments

xxv

1 Introduction to the Inverse Problems of Biometrics

(56)

1.1 Attacks on biometric systems

(7)

1.1.1 Forgery of biometric data

(1)

1.1.2 Scenario of attacks

(2)

1.1.3 Examples of forgeries

(2)

1.1.4 Trends

(2)

1.2 Classical direct and inverse problems

(3)

1.3 Direct and inverse problems of biometrics

(1)

1.3.1 Automated analysis of biometric information

(1)

1.3.2 Automated synthesis of biometric information

(1)

1.4 Basic notion of biometric data

(6)

1.4.1 Representation of biometric data

(1)

1.4.2 Description of biometric data

(1)

1.4.3 Design of synthetic biometric data

(2)

1.4.4 Artificial intelligence paradigm in synthetic biometric data design

(1)

1.5 Examples of synthetic biometric data

(5)

1.6 Conversating of biometric information

(3)

1.6.1 Types of conversions

(1)

1.6.2 Brain-machine interface

(2)

1.6.3 Implementation

(1)

1.7 Design of biometric devices and systems

(5)

1.7.1 Functions

(1)

1.7.2 Design styles for various applications

(1)

1.7.3 Architecture

(2)

1.7.4 Databases

(1)

1.8 Applications of inverse biometrics

(3)

1.8.1 Training

(1)

1.8.2 Intellectual property privacy protection

(2)

1.9 Ethical and social aspects of inverse biometrics

(1)

1.9.1 Roles for practical ethics linked to social sciences

(1)

1.9.2 Prevention of undesirable side effects

(1)

1.9.3 Targeting of areas of social concern in biometrics

(1)

1.10 Summary

(2)

1.11 Problems

(1)

1.12 Further reading

(8)

1.13 References

(9)

2 Basics of Synthetic Biometric Data Structure Design

(48)

2.1 Basic concepts of synthetic biometric data structure design

(5)

2.1.1 Topology

(1)

2.1.2 Model

(3)

2.1.3 Analysis-by-synthesis modeling

(1)

2.1.4 Acceptable and unacceptable data

(1)

2.2 Synthesis strategies

(4)

2.2.1 Assembling

(2)

2.2.2 Design based on modification of biometric data

(1)

2.2.3 Functional assembling and physical modeling

(1)

2.2.4 Testing

(1)

2.3 Information carried by biometric data

(1)

2.3.1 Categories of information

(1)

2.3.2 Measuring of information

(1)

2.4 Generation of random biometric attributes

(6)

2.4.1 The simplest noise models

(1)

2.4.2 Generation of random numbers with prescribed distributions

(3)

2.5 Degradation model in synthesis of biometric data

(2)

2.5.1 Direct and inverse models of image degradation

(1)

2.5.2 Restoration of an image containing additive noise

(1)

2.6 Image warping

(4)

2.6.1 Image warping as a topological transformation

(1)

2.6.2 Spatial transforms

(1)

2.6.3 Controlled distortion by affine transform

(2)

2.7 Deformation by interpolation and approximation

(5)

2.7.1 Parametric and implicit models

(4)

2.7.2 Generating curves by approximation

(1)

2.8 Extracting and generating features

(4)

2.8.1 Features

(2)

2.8.2 Spatial feature extraction and generation

(2)

2.9 Summary

(1)

2.10 Problems

(6)

2.11 Further reading

(5)

2.12 References

101

(4)

3 Synthetic Signatures

105

(42)

3.1 Introduction

106

(3)

3.1.1 Off-line and on-line automated signature processing

106

(2)

3.1.2 Information carried by signatures

108

(1)

3.1.3 Signature acquisition

108

(1)

3.2 Basics of signature synthesis

109

(4)

3.2.1 Signature geometry

109

(2)

3.2.2 Requirements for signature synthesis

111

(1)

3.2.3 Scenarios for signature generation

112

(1)

3.3 Signature synthesis techniques

113

(3)

3.3.1 Deformation technique

114

(1)

3.3.2 Assembling technique

114

(1)

3.3.3 Cancellable technique

115

(1)

3.4 Statistically meaningful synthesis

116

(13)

3.4.1 Preprocessing: learning

117

(1)

3.4.2 Random number generation

118

(1)

3.4.3 Geometrically meaningful synthesis

118

(7)

3.4.4 Kinematically meaningful synthesis

125

(4)

3.4.5 Postprocessing: validation

129

(1)

3.5 Implementation

129

(6)

3.6 Summary

135

(1)

3.7 Problems

136

(3)

3.8 Further reading

139

(3)

3.9 References

142

(5)

4 Synthetic Fingerprints

147

(48)

4.1 Introduction

148

(4)

4.2 Modeling a fingerprint

152

(3)

4.2.1 Topology

152

(1)

4.2.2 Information carried by the fingerprint

153

(2)

4.3 Extraction of features

155

(1)

4.4 Library of topological primitives

156

(1)

4.4.1 Terminology

157

(1)

4.4.2 Topological primitive and macroprimitive

157

(1)

4.5 Local generators: fingerprint primitives

157

(3)

4.5.1 The simplest generator of primitives based on the curve model

159

(1)

4.5.2 The simplest generator of primitives based on the spline model

159

(1)

4.6 Global generators: orientation map

160

(4)

4.6.1 Parameters of orientation map

161

(3)

4.6.2 Direct orientation transform

164

(1)

4.7 Polar transform of orientation map

164

(6)

4.7.1 Extraction of reference and center point

165

(2)

4.7.2 Polar transform

167

(1)

4.7.3 Creation of a new orientation map

168

(2)

4.8 Generating synthetic fingerprint images from an orientation map

170

(4)

4.9 Other global topological models

174

(4)

4.9.1 Master fingerprint

175

(1)

4.9.2 Simulation of noise and other conditions

176

(2)

4.10 Summary

178

(3)

4.11 Problems

181

(4)

4.12 Further reading

185

(4)

4.13 References

189

(6)

5 Synthetic Faces

195

(66)

5.1 Introduction to facial expressions design

196

(3)

5.1.1 Terminology

196

(1)

5.1.2 Applications

197

(1)

5.1.3 Modeling

197

(1)

5.1.4 Direct and inverse problems

198

(1)

5.1.5 Data structures of facial synthesis

198

(1)

5.2 Modeling of facial expressions

199

(10)

5.2.1 Basic properties of facial expressions

199

(3)

5.2.2 Components of a face model

202

(1)

5.2.3 Facial synthesis based on physical models

202

(2)

5.2.4 Facial behavior models

204

(2)

5.2.5 Library

206

(2)

5.2.6 Distribution of information sources across an object

208

(1)

5.3 Facial topology transformation and manipulation

209

(4)

5.3.1 Automated facial measurements

210

(1)

5.3.2 Morphing technique

211

(1)

5.3.3 Facial deformation

211

(1)

5.3.4 Local and global spatial transformations

211

(2)

5.4 Local facial models

213

(8)

5.4.1 Information carried by eyes, eyebrows, and lips

213

(1)

5.4.2 Eye synthesis

214

(1)

5.4.3 Eyebrow synthesis

215

(1)

5.4.4 Mouth and lips synthesis

216

(3)

5.4.5 Facial caricatures

219

(2)

5.5 Facial synthesizers

221

(4)

5.5.1 Speech-to-lips systems

222

(1)

5.5.2 Facial transmission

223

(2)

5.6 Automated support of deceit detection

225

(8)

5.6.1 Lie detection problem

225

(1)

5.6.2 Face as a carrier of false information

226

(2)

5.6.3 Models of controlled and non-controlled facial dynamics

228

(2)

5.6.4 New generation of lie detectors

230

(3)

5.7 Summary

233

(1)

5.8 Problems

234

(3)

5.9 Further reading

237

(15)

5.10 References

252

(9)

6 Synthetic Irises

261

(36)

6.1 State-of-the-art iris synthesis

262

(2)

6.1.1 Non-automated design technique

262

(1)

6.1.2 Automated design technique

263

(1)

6.2 Eye model

264

(4)

6.2.1 Structure of eye and models

265

(1)

6.2.2 Structure of iris and models

265

(3)

6.2.3 Measures

268

(1)

6.2.4 Information carried by the iris

268

(1)

6.3 Iris image preprocessing

268

(4)

6.3.1 Iris localization

269

(1)

6.3.2 Iris normalization

270

(1)

6.3.3 Iris image enhancement and noise removal

270

(1)

6.3.4 Features in analysis and synthesis

271

(1)

6.4 Iris synthesis by transformation

272

(1)

6.4.1 Recombination of iris images

272

(1)

6.4.2 Iris image warping

272

(1)

6.5 Iris synthesis by assembling

272

(11)

6.5.1 Assembling

275

(1)

6.5.2 Master iris

275

(1)

6.5.3 Library of iris colors and topological primitives

276

(1)

6.5.4 Automated generation of iris primitives

276

(1)

6.5.5 Primitive template

277

(4)

6.5.6 Using Fourier transform in collarette design

281

(2)

6.5.7 Other transforms for automated design of iris primitives

283

(1)

6.6 Summary

283

(2)

6.7 Problems

285

(6)

6.8 Further reading

291

(3)

6.9 References

294

(3)

7 Biometric Data Structure Representation by Voronoi Diagrams

297

(52)

7.1 Voronoi data structure

298

(2)

7.1.1 Topology

298

(1)

7.1.2 Computing Voronoi diagram

299

(1)

7.2 Basics of Voronoi diagram technique

300

(8)

7.2.1 Metric space

300

(2)

7.2.2 Voronoi diagram

302

(5)

7.2.3 Information carried by a Voronoi diagram

307

(1)

7.3 Direct and inverse Voronoi transform

308

(5)

7.3.1 Preliminaries

308

(2)

7.3.2 Direct Voronoi transform

310

(1)

7.3.3 Inverse Voronoi transform

310

(1)

7.3.4 Extension

311

(2)

7.4 Properties

313

(6)

7.5 Voronoi data structure in topological analysis and synthesis

319

(3)

7.6 Topological compatibility of the Voronoi diagram

322

(4)

7.6.1 Distance mapping of feature points

322

(1)

7.6.2 Distance map

323

(3)

7.7 Implementing the discrete Voronoi transform with a distance transform

326

(5)

7.7.1 Distance mapping of biometric data

329

(1)

7.7.2 Transformation of the distance map of point generators to a discrete approximation of Voronoi diagrams

329

(2)

7.8 Calculating area Voronoi diagrams using nearest-neighbor transform

331

(4)

7.8.1 Effects of approximation to Voronoi diagrams via distance transform

331

(2)

7.8.2 Nearest-neighbor map

333

(1)

7.8.3 Transformation of nearest-neighbor map of area primitives into a Voronoi diagram

334

(1)

7.9 Summary

335

(3)

7.10 Problems

338

(6)

7.11 Further reading

344

(2)

7.12 References

346

(3)

8 Synthetic DNA

349

(30)

8.1 Introduction

351

(2)

8.1.1 DNA characteristics

351

(1)

8.1.2 Ideal identification properties

351

(1)

8.1.3 Privacy issues

352

(1)

8.2 Basics of DNA biometrics

353

(3)

8.2.1 DNA code

353

(1)

8.2.2 Terminology

354

(2)

8.3 DNA/protein synthesis techniques

356

(5)

8.3.1 Mutation technique

356

(1)

8.3.2 Recombination technique

357

(2)

8.3.3 Statistically-driven synthesis

359

(2)

8.4 Examples of Markov models

361

(4)

8.4.1 0th order Markov model

361

(1)

8.4.2 1st order Markov model

362

(1)

8.4.3 2nd order Markov model

363

(2)

8.5 Postprocessing: pairwise alignments

365

(4)

8.6 Algorithm for sequence generation

369

(1)

8.7 Summary

370

(1)

8.8 Problems

371

(3)

8.9 Further reading

374

(3)

8.10 References

377

(2)

Index

379

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