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Search Publications by

Mei Lee Ngan (Fed)

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Displaying 1 - 23 of 23

Face Recognition Vendor Test (FRVT) Part 2: Identification

September 13, 2019
Patrick Grother, Mei Ngan, Kayee Hanaoka
This report updates and extends NIST Interagency Report 8238, documenting performance of new face recognition algorithms submitted for evaluation to NIST in November 2018. The algorithms implement one-to-many identification of faces appearing in two-

Ongoing Face Recognition Vendor Test (FRVT) Part 2: Identification

November 27, 2018
Patrick J. Grother, Mei L. Ngan, Kayee K. Hanaoka
This report documents performance of face recognition algorithms applied to the one-to-many identification of faces appearing in portrait images. The primary dataset is comprised of 26.6 million reasonably well controlled live photos of 12.3 million

The Text Recognition Algorithm Independent Evaluation (TRAIT)

December 15, 2017
Afzal A. Godil, Patrick J. Grother, Mei L. Ngan
The report describes and presents the results for text detection and recognition (TRAIT) evaluation in support of forensic investigations of digital media. These im- ages are of interest to NIST’s partner law enforcement agencies that seek to employ text

The 2017 IARPA Face Recognition Prize Challenge (FRPC)

November 27, 2017
Patrick J. Grother, Mei L. Ngan, Lars Ericson, Kayee K. Hanaoka, Christopher Boehnen
This report documents NIST’s execution of the Intelligence Advanced Research Projects Activity (IARPA) Face Recognition Prize Challenge 2017. The (FRPC) was conducted to assess the capability of contemporary face recognition algorithms to recognize faces

Documentation for ROC Baseline 2016

July 13, 2016
James R. Matey, Su L. Cheng, Patrick J. Grother, Mei L. Ngan, George W. Quinn, Elham Tabassi, Craig I. Watson
We present ROC baseline data to support the recommendations in Matey et al [6].

Tattoo Recognition Technology - Challenge (Tatt-C): Outcomes and Recommendations

September 15, 2015
Mei L. Ngan, George W. Quinn, Patrick J. Grother
Tattoos have been used for many years to assist law enforcement in investigations leading to the identification of both criminals and victims. A tattoo is an elective biometric trait that contains additional discriminative information to support person

IREX IV: Part 2 Compression Profiles for Iris Image Compression

January 23, 2014
George Quinn, Patrick Grother, Mei Ngan, Nick Rymer
The IREX IV evaluation builds upon IREX III as a performance test of one-to-many iris recognition. This report is the second part of the IREX IV evaluation, which specifically, evaluates the ability of automated iris recognition algorithms to match heavily

IREX IV: Part 1, Evaluation of Iris Identification Algorithms

July 11, 2013
George W. Quinn, Patrick J. Grother, Mei L. Ngan, James R. Matey
IREX IV aims to provide a fair and balanced scientific evaluation of the performance of automated iris recognition algorithms. IREX IV evaluated the performance of 66 identification (i.e. one-to-many matching) algorithms submitted by 12 companies and

IREX III - Performance of Iris Identification Algorithms

April 3, 2012
Patrick J. Grother, George W. Quinn, James R. Matey, Mei L. Ngan, Wayne J. Salamon, Gregory P. Fiumara, Craig I. Watson
Iris recognition has long been held as an accurate and fast biometric. In the first public evaluation of one-to-many iris identification technologies, this third activity in the Iris Exchange (IREX) program has measured the core algorithmic efficacy and