Automated Biometrics: Technnologies and Systems
Biometrics-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.
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Introduction to Biometrics
12 What is Biometrics?
13 How does a Biometrics System Work?
14 Where can Biometrics Systems be Applied?
15 Book Perspective
22 Physical Structures
82 Iris Recognition
83 Coordinate System
84 Texture Energy Feature
85 Experimental Results
92 Principles of Speaker Recognition
93 GSMSV Method
23 Behavioral Characteristics
24 Ways of Behaving
Signal and Image Processing
32 Transformation Technology
33 Image Enhancement
34 Image Restoration
35 Data Compression
42 Image Segmentation
43 Feature Selection
44 Pattern Classification
45 Neural Networks
52 Definitions and Notations
53 Fingerprint Image Processing
54 Minutiae Determination
55 Fingerprint Matching
62 Datum Point Determination
63 Two Typical Features in Palmprint
64 Palmprint Classification
65 Experimental Results
72 Detection and Location of Faces
73 Features Extraction and Face Recognition
74 An Dual Eigenspaces Method for Face Recognition
75 What Should We Do Next?
94 Experimental Results
102 Offline Signature
103 Online Signature
104 A Signature Verification System
105 InternetIntranet Signature Verification Application
Other Behavioral Biometrics
112 Keystroke Biometrics
113 Gesture Recognition
114 Gait Biometrics
122 HumanSide Interface
123 MachineSide Interface
132 Potential Application Areas
133 How to Select a Biometrics System
134 Application Programming Interface Standards
135 Information Resources
Biometrics Chinese Medicine
142 Four Chinese Diagnostic Methods
143 Various Observation Types in TCM
144 Tongue Diagnosis
Future Work in Biometrics
152 Key Technologies in Biometrics
153 Integrated Biometrics
154 VLSI Biometrics
Other editions - View all
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 diagnosis disease dynamic edge eigenface eigenvectors end user equal error rates face image face recognition feature extraction feature vectors filter finger fingerprint image function Gabor filters gait gesture global speaker model gray level hand geometry Hidden Markov Models 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 palm parameters Pattern Recognition performance personal identification pixel principal line problem Proc pulse re-estimation recognition system reference speaker ridges sample segments sequence shown in Figure signal speaker recognition speaker verification speech techniques template threshold Traditional Chinese Medicine transform types voice