Signal and image processing for biometrics

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Publication Information:

London : ISTE ; Hoboken, N.J. : Wiley, 2012

Physical Description:

xvi, 319 p. : ill. ; 24 cm.

ISBN:

9781848213852

Subject Term:

Biometric identification

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010306244	TK7882.B56 S54 2012	Open Access Book	Book	Searching... Unknown

The aim of this book is to deal with biometrics in terms of signal and image processing methods and algorithms. This will help engineers and students working in digital signal and image processing deal with the implementation of such specific algorithms.

It discusses numerous signal and image processing techniques that are very often used in biometric applications. In particular, algorithms related to hand feature extraction, speech recognition, 2D/3D face biometrics, video surveillance and other interesting approaches are presented. Moreover, in some chapters, Matlab codes are provided so that readers can easily reproduce some basic simulation results.

This book is suitable for final-year undergraduate students, postgraduate students, engineers and researchers in the field of computer engineering and applied digital signal and image processing.

1. Introduction to Biometrics, Bernadette Dorizzi.
2. Introduction to 2D Face Recognition, Amine Nait-Ali and Dalila Cherifi.
3. Facial Soft Biometrics for Person Recognition, Antitza Dantcheva, Christelle Yemdji, Petros Elia and Jean-Luc Dugelay.
4. Modeling, Reconstruction and Tracking  for Face Recognition, Catherine Herold, Vincent Despiegel, Stéphane Gentric, Séverine Dubuisson and Isabelle Bloch.
5. 3D Face Recognition, Mohsen Ardabilian, Przemyslaw Szeptycki, Di Huang and Liming Chen.
6. Introduction to Iris Biometrics, Kamel Aloui, Amine Nait-Ali, Régis Fournier and Saber Naceur.
7. Voice Biometrics: Speaker Verification and Identification, Foezur Chowdhury, Sid-Ahmed Selouani and Douglas O'Shaughnessy.
8. Introduction to Hand Biometrics, Régis Fournier and Amine Nait-Ali.
9. Multibiometrics, Romain Giot, Baptiste Hemery, Estelle Cherrier and Christophe Rosenberger.
10. Hidden Biometrics, Amine Nait-Ali, Régis Fournier, Kamel Aloui and Noureddine Belgacem.
11. Performance Evaluation of Biometric Systems, Mohamad El-Abed, Romain Giot, Baptiste Hemery, Julien Mahier and Christophe Rosenberger.
12. Classification Techniques for Biometrics, Amel Bouchemha, Chérif Nait-Hamoud, Amine Nait-Ali and Régis Fournier.
13. Data Cryptography, Islam Naveed and William Puech.
14. Visual Data Protection, Islam Naveed and William Puech.
15. Biometrics in Forensics, Guillaume Galou and Christophe Lambert.

Author Notes

Amine Nait-Ali is Professor at University Paris-Est Crteil in France. His research interests focus on biosignal processing, biometrics modeling, pattern recognition and multimodal compression. He has edited and co-edited numerous books and co-authored peer-reviewed papers I the bio-engineering field. Currently, he is in charge of a biometric research group and an international Masters program in biometrics.
Rgis Fournier is Associate Professor at University Paris Est Crteil in France. His research interests concern biosignal processing, modeling, stochastic processes, multimodal compression and biometrics. He has co-authored national and international peer-reviewed papers in the biomedical engineering field. A member of a biometric research group, he is currently involved in scientific relationships with companies for an international Masters program in biometrics

Amine Naït-Ali and Régis FournierBemadette DorizziAmine Naït-Ali and Dalila CherifiAntitza Dantcheva and Christelle Yemdji and Petros Ella and Jean-Luc DugelayMohsen Ardabilian and Przemyslaw Szeptycki and Di Huang and Liming ChenKamel Aloui and Amine Naït-Ali and Régis Fournier and Saber NaceurRégis Fournier and Amine Naït-AliRomain Giot and Baptiste Hemery and Estelle Cherrier and Christophe RosenbergerAmine Naït-Ali and Régis Fournier and Kamel Aloui and Noureddine BelgacemMohamad El Abed and Romain Giot and Baptiste Hemery and Julien Mahier and Christophe RosenbergerAmel Bouchemha and Cherif Nait-Hamoud and Amine Naït-Ali and Régis FouknierIslam Naveed and William PuechIslam Naveed and William PuechGuillaume Galou and Christophe Lambert

Preface	p. xiii
Chapter 1 Introduction to Biometrics	p. 1
1.1 Background: from anthropometry to biometrics	p. 1
1.2 Biometrics today	p. 2
1.3 Different modes of use of a biometric system and associated uses	p. 3
1.4 Biometrics as a pattern recognition problem	p. 4
1.4.1 Capture module: from the sensor to the image	p. 5
1.4.2 From the image to the features	p. 6
1.4.3 The matching	p. 7
1.5 Evaluation of different modalities	p. 8
1.6 Quality	p. 9
1.7 Multimodality	p. 10
1.8 Biometrics and preservation of privacy	p. 11
1.9 Conclusion	p. 12
1.10 Bibliography	p. 12
Chapter 2 Introduction to 2D Face Recognition	p. 15
2.1 Introduction	p. 15
2.2 Global face recognition techniques	p. 16
2.2.1 Principal component analysis	p. 16
2.2.2 Face recognition using PCA	p. 19
2.2.3 Linear discriminant analysis	p. 24
2.2.4 Face recognition using LDA	p. 24
2.3 Local face recognition techniques	p. 25
2.3.1 Geometric techniques	p. 25
2.3.2 Elastic graph matching techniques	p. 26
2.4 Hybrid face recognition techniques	p. 28
2.5 Some guidances	p. 32
2.6 Some databases	p. 35
2.7 Conclusion	p. 35
2.8 Bibliography	p. 36
Chapter 3 Facial Soft Biometrics for Person Recognition	p. 39
3.1 Introduction to soft biometrics	p. 39
3.1.1 Domains of application	p. 40
3.1.2 Related work	p. 41
3.2 Soft biometric systems for human identification	p. 42
3.2.1 Spread of the category set $	p. 43
3.2.2 Bounding N for a given interference probability	p. 45
3.2.3 Simulation evaluation of the system in the interference-limited setting of very high sensor resolution	p. 47
3.3 Overall error probability of a soft biometrics system	p. 48
3.3.1 P err of a soft biometric system in a frontal-to-side re-identification scenario	p. 50
3.4 Conclusions and future directions	p. 53
3.5 Bibliography	p. 53
Chapter 4 Modeling, Reconstruction and Tracking for Face RecognitionCatherine Herold and Vincent Despiegel and Stephane Gentric and Severine Dubuisson
4.1 Background	p. 57
4.1.1 Applications of face recognition	p. 58
4.1.2 On-the-fly authentication	p. 58
4.2 Types of available information	p. 61
4.2.1 Information related to the acquisition system	p. 61
4.2.2 Facial features	p. 62
4.3 Geometric approaches for the reconstruction	p. 63
4.3.1 Stereovision - Multiview	p. 63
4.3.2 Shape from shading	p. 65
4.4 Model-based approaches for reconstruction	p. 67
4.4.1 Modeling of the face	p. 67
4.4.2 Estimation of the model parameters	p. 70
4.5 Hybrid approaches	p. 76
4.6 Integration of the time aspect	p. 77
4.6.1 Face tracking	p. 77
4.6.2 Static approach from video streams	p. 79
4.6.3 Time consolidation from video streams	p. 81
4.7 Conclusion	p. 82
4.8 Bibliography	p. 83
Chapter 5 3D Face Recognition	p. 89
5.1 Introduction	p. 89
5.2 3D face databases	p. 90
5.2.1 FRGC	p. 91
5.2.2 GavabDB	p. 91
5.2.3 3DTEC	p. 92
5.3 3D acquisition	p. 92
5.4 Preprocessing and normalization	p. 94
5.4.1 Sensor noise processing	p. 95
5.4.2 Processing of holes	p. 96
5.4.3 Localization of anthropometric landmarks	p. 96
5.5 3D face recognition	p. 101
5.5.1 3D face recognition based on local features matching: a case study	p. 102
5.6 Asymmetric face recognition	p. 109
5.7 Conclusion	p. 110
5.8 Bibliography	p. 111
Chapter 6 Introduction to Iris Biometrics	p. 117
6.1 Introduction	p. 117
6.2 Iris biometric systems	p. 118
6.3 Iris recognition methods: state-of-the-art	p. 119
6.4 Preprocessing of iris images	p. 122
6.4.1 Extraction of the region of interest	p. 122
6.4.2 Construction of the noise mask	p. 123
6.4.3 Normalization	p. 124
6.5 Features extraction and encoding	p. 125
6.6 Similarity measure between two IrisCodes	p. 126
6.7 Iris biometrics: emerging methods	p. 127
6.8 Conclusion	p. 128
6.9 Bibliography	p. 128
Chapter 7 Voice Biometrics: Speaker Verification and IdentificationFoezur Chowdhury and Sid-Ahmed Selouani
7.1 Introduction	p. 131
7.1.1 Voice biometric techniques	p. 132
7.1.2 Challenge of speaker recognition on mobile devices	p. 133
7.2 Acoustic analysis for robust speaker recognition	p. 134
7.2.1 Mel-frequency analysis	p. 135
7.2.2 Wiener filtering for noise reduction	p. 137
7.3 Distributed speaker recognition through UBM-GMM models	p. 138
7.3.1 Bayesian adaptation to target models	p. 139
7.3.2 Scoring technique for speaker identification	p. 140
7.3.3 Likelihood ratio for speaker verification	p. 140
7.3.4 Normalization of the verification score and Z-norm	p. 141
7.4 Performance evaluation of DSIDV	p. 142
7.4.1 Corpus	p. 142
7.4.2 Experimental protocol	p. 142
7.4.3 Experimental results	p. 143
7.5 Conclusion	p. 145
7.6 Bibliography	p. 146
Chapter 8 Introduction to Hand Biometrics	p. 149
8.1 Introduction	p. 149
8.2 Characterization by minutiae extraction	p. 151
8.2.1 Histogram equalization	p. 151
8.2.2 Binarization	p. 154
8.2.3 Skeletonization (thinning)	p. 156
8.2.4 Detection of minutiae	p. 157
8.2.5 Matching	p. 159
8.2.6 Evaluation of performances	p. 160
8.3 A few databases	p. 160
8.3.1 Fingerprint verification competition (FVC 2000, 2002, 2004, 2006)	p. 161
8.3.2 CASIA fingerprint	p. 162
8.3.3 Wet and wrinkled fingerprint	p. 162
8.3.4 The HK Polytechnic University fingervein image database [HKF]	p. 162
8.3.5 CASIA palmprint (visible/multispectral)	p. 162
8.3.6 Database (THUPALMLAB)	p. 163
8.4 Conclusion	p. 165
8.5 Bibliography	p. 165
Chapter 9 Multibiometrics	p. 167
9.1 Introduction	p. 167
9.2 Different principles of multibiometrics	p. 169
9.3 Fusion levels	p. 171
9.3.1 Capture fusion	p. 171
9.3.2 Feature fusion	p. 175
9.3.3 Score fusion	p. 177
9.3.4 Fusion of decision and rank	p. 184
9.3.5 Evaluation	p. 187
9.4 Applications and illustrations	p. 189
9.5 Conclusion	p. 191
9.6 Bibliography	p. 192
Chapter 10 Hidden Biometrics	p. 195
10.1 Introduction	p. 195
10.2 Biometrics using ECG	p. 196
10.3 Biometrics using EMG: preliminary experiments	p. 198
10.4 Biometrics using medical imaging	p. 200
10.4.1 Biometrics using MRI images	p. 200
10.4.2 Biometrics with X-ray images	p. 203
10.5 Conclusion	p. 205
10.6 Bibliography	p. 205
Chapter 11 Performance Evaluation of Biometric Systems	p. 207
11.1 Introduction	p. 207
11.2 Reminders on biometric systems	p. 208
11.2.1 Biometrics	p. 208
11.2.2 Biometric characteristics	p. 209
11.2.3 Biometric models	p. 209
11.2.4 Enrollment, verification and identification	p. 210
11.2.5 Architecture of a biometric system	p. 211
11.3 Results analysis tools	p. 212
11.3.1 Performance of biometric systems	p. 212
11.3.2 Benchmarks	p. 222
11.4 Illustration of the GREYC-Keystroke system	p. 223
11.4.1 Evaluation protocol	p. 223
11.4.2 Experimental results	p. 226
11.5 Conclusion	p. 228
11.6 Bibliography	p. 229
Chapter 12 Classification Techniques for Biometrics	p. 231
12.1 Introduction	p. 231
12.2 Generalization aptitude and performance measures	p. 232
12.3 Parametric approaches	p. 234
12.3.1 Naive Bayesian classification	p. 234
12.3.2 Linear discriminant analysis	p. 236
12.4 Non-parametric approaches	p. 241
12.4.1 KNN classifier	p. 241
12.4.2 Classification using artificial neural networks	p. 243
12.4.3 Support vector machine	p. 250
12.5 Conclusion	p. 260
12.6 Bibliography	p. 261
Chapter 13 Data Cryptography	p. 263
13.1 Introduction	p. 263
13.2 Cryptography	p. 263
13.2.1 Introduction to modem cryptography	p. 264
13.2.2 Definitions	p. 265
13.2.3 Classification of modern crytography	p. 265
13.2.4 Cryptanalysis	p. 275
13.3 Conclusion	p. 276
13.4 Bibliography	p. 276
Chapter 14 Visual Data Protection	p. 279
14.1 Introduction	p. 279
14.2 Visual data hiding	p. 279
14.2.1 Digital watermarking	p. 280
14.2.2 Digital fingerprinting	p. 282
14.3 A proposed homomorphism-based visual secret sharing scheme	p. 284
14.3.1 Image encryption procedure in the proposed scheme	p. 285
14.3.2 The proposed image sharing scheme	p. 285
14.3.3 Experimental results and discussion	p. 291
14.4 Conclusion	p. 294
14.5 Bibliography	p. 294
Chapter 15 Biometrics in Forensics	p. 297
15.1 Introduction	p. 297
15.2 Facial comparison	p. 298
15.2.1 Biometrics dedicated to forensic approximation	p. 298
15.2.2 The problem of facial comparison for forensic assessment	p. 299
15.3 Voice comparison in forensics	p. 301
15.3.1 Introduction	p. 301
15.3.2 Particularities of the voice modality in the field of biometrics	p. 302
15.3.3 Voice comparison and forensic assessment	p. 304
15.3.4 Inference of identity in forensics	p. 304
15.3.5 Automatic voice comparison	p. 306
15.3.6 Conclusion	p. 311
15.4 Bibliography	p. 311
List of Authors	p. 313
Index	p. 317

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