Take a sneak peek at the new NIST.gov and let us know what you think!
(Please note: some content may not be complete on the beta site.).
Biometric Quality Homepage
Performance of biometric systems is dependent on the quality of the acquired input samples. If quality can be improved, either by sensor design, by user interface design, or by standards compliance, better performance can be realized. For those aspects of quality that cannot be designed-in, an ability to analyze the quality of a live sample is needed. This is useful primarily in initiating the reacquisition from a user, but also for the real-time selection of the best sample, and the selective invocation of different processing methods. It is the key component in quality assurance management, and because quality algorithms often embed the same image (or signal) analyses needed to assess conformance to underlying data interchange standards, they can be used in automated image screening applications.
Quality analysis is a technical challenge because it is most helpful when the measures reflect the performance sensitivities of one or more target biometric matchers. NIST addressed this problem in August 2004 when it issued the NIST Fingerprint Image Quality algorithm, which was designed to be predictive of the performance of minutiae matchers. Since then NIST has been considering how quality measures should be evaluated, developing quality measures for other biometrics, and considering the wider use of such measures. In addition NIST is active in the new SC37 and M1 standardization activities on biometric quality and sample conformance.
NIST announces the development of NFIQ 2.0
NFIQ was developed in 2004 to produce a quality value from a fingerprint image that is directly predictive of expected matching performance. With advances in fingerprint technology since 2004, an update to NFIQ is needed. A workshop was held in March 2010 at NIST to address the technical status of fingerprint quality assessment technology, and to engage industry to improve core finger image quality assessment technology based on lessons learned from recent deployments of quality assessment algorithms (including NFIQ) in large-scale identity management applications. Options for the future of NFIQ were discussed and the community overwhelmingly recommended a new (open source) version of NFIQ to be developed in consultation and collaboration with users and industry. To that end, National Institute of Standards and Technology (NIST) and Bundesamt für Sicherheit in der Informationstechnik (BSI) in Germany have teamed up to develop the new and improved open source NIST Finger Image Quality (NFQ 2.0) and extend invitation to research organizations and industry members to provide specific support in the development of NFIQ 2.0. Please see the call for participation for more detail. Please send your suggestions and/or comments to email@example.com .
Biometric Quality Links