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Information Technology

Biometrics

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  • Published Date
Displaying 201 - 225 of 804

JPEG 2000 CODEC Certification Guidance for 1000 ppi Fingerprint Friction Ridge Imagery

June 4, 2015
Author(s)
Shahram Orandi, John M. Libert, Michael Garris, John Grantham, Frederick R. Byers
The document describes the procedure by which applications of JPEG 2000 CODECs will be evaluated with respect to conformance to the NIST guidance for compression of 1000 ppi friction ridge images as detailed in NIST Special Publication 500-289 [NIST5]

Evaluating automatic face recognition systems with human benchmarks

April 9, 2015
Author(s)
P. Jonathon Phillips, Alice O'Toole
Human face recognition skills are often considered the gold standard against which machines must compete. Over the last two decades, however, international tests of computer-based face recognition algorithms have shown steady improvements in accuracy with

Report on the FG 2015 Video Person Recognition Evaluation

April 2, 2015
Author(s)
P J. Phillips, J. R. Beveridge, Hao Zhang, Bruce A. Draper, Patrick J. Flynn, Zhenhua Feng, Patrik Huber, Josef Kittler, Zhiwu Huang, Shaoxin Li, Yan Li, Meina Kan, Ruiping Wang, Shiguang Shan, Xilin Chen, Haoxiang Li, Hua Gang, Vitomir Struc, Janez Krizaj, Changxing Ding, Dacheng Tao

Fingerprint Vendor Technology Evaluation

January 8, 2015
Author(s)
Craig I. Watson, Gregory P. Fiumara, Elham Tabassi, Su L. Cheng, Patricia A. Flanagan, Wayne J. Salamon
FpVTE was conducted primarily to assess the current capabilities of fingerprint matching algorithms using operational datasets containing several million subjects. There were three classes of participation that examined various finger combinations from

Generalizing Face Quality and Factor Measures to Video

September 24, 2014
Author(s)
Yooyoung Lee, P. Jonathon Phillips, James Filliben, J. R. Beveridge, Hao H. Zhang
Methods for assessing the impact of factors and image-quality metrics for still face images are well-understood. The extension of these factors and quality measures to faces in video has not, however, been explored. We present a specific methodology for