Given the importance of biometric sample quality assessment in improving performance of operational systems, quality algorithms are being increasingly deployed: US-VISIT, PIV, and EU VIS. Each mandate the measurement and reporting of quality scores of captured images. Accordingly quality is the subject of active research. In addition biometric quality standardization is underway (ISO/IEC 29794) with the aim of uniform interpretation and interoperability of quality scores. In order to discuss capabilities vis-a-vis operational requirements, and to identify research needs, testing requirements, and standardization gaps. The workshop was a forum for experts to share their research and discuss problems and new developments. The workshop was a sequel to the workshop on quality NIST hosted in March 2006. Since then, NIST has been developing methods for quality summarization in support of quality monitoring, measuring quality of slap fingerprints, and has studied the role of human factors in quality. In addition, NIST is active in the SC37 and M1 standardization activities on biometric quality and sample conformance.
The workshop aimed at improving accuracy of biometric systems by incorporating quality assessment technologies into the sample acquisition process. It aimed to assess current quality measurement capabilities and to identify technologies, factors, operational paradigms, and standards that can measurably improve quality. The format was different from that of the 2006 Quality Workshop I : shorter presentations followed by discussions. We focused on the following issues:
The workshop is organized by the Information Access Division of the Information Technology Laboratory (ITL) at the National Institute of Standards and Technology (NIST).
The workshop is supported by the Department of Homeland Security (DHS), the Department of State (DOS), the Federal Bureau of Investigation (FBI), the Department of Defense, Biometric Task Force, and the National Science and Technology Council (NSTC) Subcommittee on Biometrics and Identity Management.