Biometric Systems: Technology, Design and Performance Evaluation
James L. Wayman, Anil K. Jain, Davide Maltoni, Dario Maio
Springer Science & Business Media, Dec 6, 2005 - Computers - 370 pages
The use of computers to recognize humans from physical and behavioral traits dates back to the digital computer evolution of the 1960s. But even after decades of research and hundreds of major deployments, the field of biometrics remains fresh and exciting as new technologies are developed andoldtechnologiesareimprovedandfieldedinnewapplications.Wor- wide over the past few years,there has been a marked increase in both g- ernment and private sector interest in large-scale biometric deployments for accelerating human–machine processes, efficiently delivering human services, fighting identity fraud and even combating terrorism. The p- pose of this book is to explore the current state of the art in biometrics- tems and it is the system aspect that we have wished to emphasize. By their nature, biometric technologies sit at the exact boundary of the human–machineinterface.Butlikealltechnologies,bythemselvestheycan provide no value until deployed in a system with support hardware, n- work connections, computers, policies and procedures, all tuned together to work withpeople to improve some real business process within a social structure.
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35 mm film AFIS Analysis and Machine application approach automated Available online Average enroll baseline algorithm biometric systems classification Computer Vision EER EER Eigenface electret error rates experimental algorithms face recognition FERET database FERET evaluations Figure filtering finger fingerprint image Fingerprint Verification Competition FMR FNMR FNMR FMR Score distributions FNMR(t FRVT Gabor filter gallery and probe Genuines FMR FNMR hand geometry handset IEEE IEEE Trans Impostors Genuines FMR individual iris recognition meta-analysis methods minutiae NGRA NIRA REJNGRA NIRA REJNGRA REJNIRA NIST one-speaker detection participants Pattern Analysis performance personal data pixels probe set problem Proc recognition systems REJENROLL NGRA NIRA REJNGRA REJNIRA 0.00 ROC curve Algorithm sample Score distributions FMR(t seconds Average match seconds REJENROLL NGRA sensor speaker recognition speaker verification speech target speaker target trials techniques template test segment threshold 10-5 tion training data ZeroFMR ZeroFNMR