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Advances in Biometrics

eBook - Sensors, Algorithms and Systems

Erschienen am 06.10.2007, 1. Auflage 2007
111,95 €
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Bibliografische Daten
ISBN/EAN: 9781846289217
Sprache: Englisch
Umfang: 508 S., 47.24 MB
E-Book
Format: PDF
DRM: Digitales Wasserzeichen

Beschreibung

Biometrics technology continues to stride forward with its wider acceptance and its perceived need in various new security facets of modern society. Biometrics is being required to meet the growing challenges of identity management. While biometrics finds use in all diverse applications, the research challenges continue to grow as the user community expects a fully automatic system to cover the whole universal population with almost no errors.

Recent advances in biometrics include new developments in sensors, modalities and algorithms. As new sensors are designed, newer challenges emerge in the algorithms for accurate recognition. New modalities have been discovered in addition to the fusion of existing modalities to improve accuracy and wider coverage.

Written for researchers, advanced students and practitioners to use as a handbook, this volume captures the very latest state-of-the-art research contributions from leading international researchersin the field.

Autorenportrait

Dr Nalini K. Ratha is a Research Staff Member at the IBM Thomas J. Watson Research Center, Yorktown Heights, New York. His current research interests include biometrics, computer vision, pattern recognition and special purpose architecture for computer vision systems. He leads the biometrics research effort in the area of enhancing security of biometrics systems and performance evaluation of biometrics systems. He has co-edited a book entitled "Automatic Fingerprint Recognition Systems" published by Springer and co-authored a book entitled "A guide to Biometrics Selection and System design" published by Springer in 2003. He was also general co-chair of IEEE AutoID 02 and SPIE Conf. on Biometrics in Human Identification 2004. He has received several patent awards and a "Research Division" award at IBM.

He received his Ph. D. from the Department of Computer Science at Michigan State University and B.Tech in Electrical Engineering and M. Tech in Computer science and Engineering from Indian Institute of Technology, Kanpur. He is a senior member of IEEE and co-chair of AutoID TC, IEEE Robotics and Automation Society.

 

Dr. Venu Govindaraju is a Professor of Computer Science and Engineering at the University at Buffalo (UB), State University of New York. He received his B-Tech (Honors) from the Indian Institute of Technology (IIT), Kharagpur, India in 1986, and his Ph.D. degree in Computer Science from UB in 1992.

Govindaraju has co-authored more than 200 scientific papers. He is the PI on current NSF sponsored projects on International Digital Libraries and Digital Government. He is the founding director of the Center for Unified Biometrics and Sensors (CUBS).

He serves on the editorial boards of the IEEE Transactions on Systems, Man, and Cybernetics (B), the International Journal for Document Analysis and Recognition, The Journal of Pattern Analysis and Applications andThe Journal of Pattern Recognition.

Inhalt

Sensors.- Multispectral Fingerprint Image Acquisition.- Touchless Fingerprinting Technology.- A Single-Line AC Capacitive Fingerprint Swipe Sensor.- Ultrasonic Fingerprint Sensors.- Palm Vein Authentication.- Finger Vein Authentication Technology and Financial Applications.- Iris Recognition in Less Constrained Environments.- Ocular Biometrics: Simultaneous Capture and Analysis of the Retina and Iris.- Face Recognition Beyond the Visible Spectrum.- Algorithms.- Voice-Based Speaker Recognition Combining Acoustic and Stylistic Features.- Conversational Biometrics: A Probabilistic View.- Function-Based Online Signature Verification.- Writer Identification and Verification.- Improved Iris Recognition Using Probabilistic Information from Correlation Filters.- Headprint-Based Human Recognition.- Pose and Illumination Issues in Face- and Gait- Based Identification.- SVDD-Based Face Reconstruction in Degraded Images.- Strategies for Improving Face Recognition from Video.- Large-Population FaceRecognition (LPFR) Using Correlation Filters.- Systems.- Fingerprint Synthesis and Spoof Detection.- Match-on-Card for Secure and Scalable Biometric Authentication.- Privacy and Security Enhancements in Biometrics.- Adaptive Biometric Systems That Can Improve with Use.- Biometrics Standards.

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