Automated Biometrics: Technnologies and SystemsBiometrics-based authentication and identification are emerging as the most reliable method to authenticate and identify individuals. Biometrics requires that the person to be identified be physically present at the point-of-identification and relies on `something which you are or you do' to provide better security, increased efficiency, and improved accuracy. Automated biometrics deals with physiological or behavioral characteristics such as fingerprints, signature, palmprint, iris, hand, voice and face that can be used to authenticate a person's identity or establish an identity from a database. With rapid progress in electronic and Internet commerce, there is also a growing need to authenticate the identity of a person for secure transaction processing. Designing an automated biometrics system to handle large population identification, accuracy and reliability of authentication are challenging tasks. Currently, there are over ten different biometrics systems that are either widely used or under development. Some automated biometrics, such as fingerprint identification and speaker verification, have received considerable attention over the past 25 years, and some issues like face recognition and iris-based authentication have been studied extensively resulting in successful development of biometrics systems in commercial applications. However, very few books are exclusively devoted to such issues of automated biometrics. Automated Biometrics: Technologies and Systems systematically introduces the technologies and systems, and explores how to design the corresponding systems with in-depth discussion. The issues addressed in this book are highly relevant to many fundamental concerns of both researchers and practitioners of automated biometrics in computer and system security. |
Contents
Introduction to Biometrics | 1 |
12 What is Biometrics? | 2 |
13 How does a Biometrics System Work? | 8 |
14 Where can Biometrics Systems be Applied? | 13 |
15 Book Perspective | 16 |
References | 18 |
Biometrics Technologies | 23 |
22 Physical Structures | 27 |
82 Iris Recognition | 161 |
83 Coordinate System | 165 |
84 Texture Energy Feature | 168 |
85 Experimental Results | 171 |
References | 177 |
Behavioral Biometrics | 179 |
92 Principles of Speaker Recognition | 180 |
93 GSMSV Method | 186 |
23 Behavioral Characteristics | 36 |
24 Ways of Behaving | 39 |
References | 42 |
Signal and Image Processing | 43 |
32 Transformation Technology | 44 |
33 Image Enhancement | 47 |
34 Image Restoration | 52 |
35 Data Compression | 56 |
References | 61 |
Pattern Recognition | 63 |
42 Image Segmentation | 64 |
43 Feature Selection | 71 |
44 Pattern Classification | 73 |
45 Neural Networks | 78 |
References | 84 |
Physical Biometrics | 87 |
52 Definitions and Notations | 88 |
53 Fingerprint Image Processing | 92 |
54 Minutiae Determination | 96 |
55 Fingerprint Matching | 105 |
References | 107 |
Palmprint Verification | 111 |
62 Datum Point Determination | 114 |
63 Two Typical Features in Palmprint | 118 |
64 Palmprint Classification | 128 |
65 Experimental Results | 132 |
References | 134 |
Face Recognition | 137 |
72 Detection and Location of Faces | 139 |
73 Features Extraction and Face Recognition | 146 |
74 An Dual Eigenspaces Method for Face Recognition | 152 |
75 What Should We Do Next? | 155 |
References | 156 |
Iris Biometrics | 159 |
94 Experimental Results | 194 |
References | 200 |
Signature System | 203 |
102 Offline Signature | 205 |
103 Online Signature | 208 |
104 A Signature Verification System | 211 |
105 InternetIntranet Signature Verification Application | 216 |
References | 225 |
Other Behavioral Biometrics | 227 |
112 Keystroke Biometrics | 229 |
113 Gesture Recognition | 231 |
114 Gait Biometrics | 234 |
References | 239 |
Biometrics Applications | 243 |
122 HumanSide Interface | 246 |
123 MachineSide Interface | 254 |
PalmScanner Interface | 261 |
References | 266 |
Personal Authentication | 269 |
132 Potential Application Areas | 271 |
133 How to Select a Biometrics System | 274 |
134 Application Programming Interface Standards | 279 |
135 Information Resources | 286 |
Biometrics Chinese Medicine | 289 |
142 Four Chinese Diagnostic Methods | 291 |
143 Various Observation Types in TCM | 295 |
144 Tongue Diagnosis | 298 |
| 310 | |
Future Work in Biometrics | 313 |
152 Key Technologies in Biometrics | 314 |
153 Integrated Biometrics | 319 |
154 VLSI Biometrics | 322 |
| 327 | |
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Common terms and phrases
algorithm Analysis approaches automatic behavioral biometrics bifurcations biometrics applications biometrics system biometrics technology blood capture characteristics Chinese Medicine classification compression Computer Vision data compression database detection device disease dynamic edge eigenface eigenvectors end user equal error rates face image face recognition feature extraction feature points feature vectors filter finger fingerprint image function Gabor filters gait gesture global speaker model gray level hand geometry histogram human IEEE IEEE Trans Image Processing input interface International Iris Recognition layer likelihood score line feature matching minutiae neural network noise normal on-line signature verification output palm parameters Pattern Recognition performance personal identification pixel principal line problem Proc pulse re-estimation recognition system reference speaker ridge sample segments sequence shown in Figure signal speaker recognition speaker verification speech techniques template threshold Traditional Chinese Medicine transform types voice