NIST has an exciting volunteer opportunity for local citizens to help support first responder technology. We welcome and encourage people to sign up with friends, family, and colleagues. Anyone over the age of 17 who is a US Citizen or Permanent Resident (green card holder) may participate. This is a great opportunity to help first responders and visit a NIST research facility! Here’s the pitch –
PUBLIC SAFETY RESEARCHERS NEED YOUR FINGERPRINTS – Collection week is April 18-22
Help Our First Responders! Volunteer your fingerprints to advance mobile fingerprint capture technology to help first responders efficiently collect and process fingerprints in the field. NIST Public Safety Communications Research Division (PSCR) needs fingerprint images from many volunteers to evaluate contestants’ final phase prototypes in the Mobile Fingerprinting Innovation Technology (mFIT) Challenge. Volunteers will provide their fingerprints on 12 prototypes in exchange for a “Good Deed feeling” and snacks to go.
Sign up for a time slot on SignUp Genius. Time slots are on the hour at 9, 10, and 11 AM as well as 1, 2, and 3 PM each day, M-F, April 18-22. We estimate collection time at 45 minutes with up to six volunteers in each group. This event is open to all US citizens or Permanent Residents over 17 years old! Organize your group to sign up together – think Team Event! Our outdoor patio is a great place for your group to socialize after your appointment.
Our safety protocol is extensive, including prototype cleaning between each volunteer. We ask all participants to attest to completing the Personal Daily COVID-19 Screening Questionnaire. The collected fingerprint data will be fully anonymized, meaning fingerprint data will not be associated with any individual’s data. Volunteers will receive a random identifier when they arrive at the check-in desk. The fingerprint data will only be used in the PSCR lab, stored on secure drives on the PSCR dedicated research network, and not shared outside of NIST. PSCR will delete the fingerprint images after we complete evaluations.
Download the Updated Supplemental Submission Requirements & Recommendations document to help guide your submission for Phase 2 of the competition.
Reminder that Phase 2 submissions are due to NIST PSCR by April 4, 2022.
Download the Letter of Intent.
You must email your signed Letter of Intent to firstname.lastname@example.org by March 14, 2022 to confirm your participation in Phase 2.
 Certified Products List. FBI Biometric Specifications. (2021, June 28). https://www.fbibiospecs.cjis.gov/certifications
 Majumder, S., & Deen, M. J. (2019, May 9). Smartphone Sensors for Health Monitoring and Diagnosis. PubMed Central. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539461/
 Electric Biometric Transmission Specification. FBI Biometric Specifications. https://www.fbibiospecs.cjis.gov/EBTS/Approved
Libert, J.M., Grantham, J.D., Bandini, B., Ko, K., Orandi, S., Watson, C. (May 2020) Interoperability Assessment 2019: Contactless-to-Contact Fingerprint Capture. NIST Pubs. https://doi.org/10.6028/NIST.IR.8307
Orandi, S., Libert, J.M., Bandini, B., Ko, K., Grantham, J.D., Watson, C. (September 2020) Evaluating the Operational Impact of Contactless Fingerprint Imagery on Matcher Performance. NIST Pubs. https://doi.org/10.6028/NIST.IR.8315
Orandi, S., Watson, C., Libert, J.M., Fiumara, G.P., Grantham, J.D. (March 2021) Contactless Fingerprint Capture and Data Interchange Best Practice Recommendation. NIST Pubs. https://doi.org/10.6028/NIST.SP.500-334
Libert, J.M., Grantham, J.D., Bandini, B., Wood, S., Garris, M., Ko, K., Byers, F., Watson, C. (July 2018) Guidance for Evaluating Contactless Fingerprint Acquisition Devices. NIST Pubs. https://doi.org/10.6028/NIST.SP.500-305
This challenge encourages contestants to provide innovative solutions that support the unique requirements of law enforcement officers. In preparation for this challenge, PSCR worked with multiple subject matter experts (SMEs) to understand the current state of the technology and identify technical gaps or barriers that are inhibiting advances in capturing digital fingerprints on mobile devices. While contestants are encouraged to bridge these gaps, contestants are also encouraged to explore and innovate in any area that would improve the accuracy and quality of the fingerprint capture technology. The SMEs identified the following technology gaps:
Accurate contactless fingerprint capture requires knowing the precise distance from the camera to the finger. Utilization of a device’s onboard sensors such as the video camera and distance meter (e.g., Time of Flight or LIDAR) may be used to aid in accurate fingerprint capture. Code that utilizes these sensors could provide the ability to capture necessary image detail.
Distortion based on finger pose and shape degrades the usability of fingerprints for accurate matching. Photometric distortion causes missing areas and spurious minutiae points, while geometric distortion manipulates the spatial location of features. Image processing algorithms could be used to establish the pose and position of the hand and fingers to improve optical recognition.
Algorithms used for the rendering of images from mobile device sensors can be computationally intense, and novel solutions could increase this complexity. New methodologies and algorithm improvements can enable rendering using the modest computation capability of mobile devices.
Modern mobile devices feature several sensors such as high-resolution and high-speed CMOS (complementary metal oxide semiconductor) image sensors, a GPS sensor, accelerometer, gyroscope, magnetometer, ambient light sensor, microphone, distance measuring sensors, and fingerprint sensor . Contestants are encouraged to use available sensors on a mobile device that will improve the quality of fingerprint images. Another sensor available on some devices is an ultrasonic fingerprint scanning sensor; however, this device sensor is currently only used for smartphone authentication purposes and is not available to 3rd party applications. The potential for the use of ultrasonic fingerprint scanning sensors is demonstrated by Qualcomm’s device certified by the FBI EBTS . While this device was specially engineered for use by the Department of Defense and is a different form factor than smartphones and tablets, it demonstrates the use of ultrasonic technology in capturing quality digital fingerprint images.
The mFIT Challenge will allow the addition of sensors that are not currently available on mobile devices but have the potential to be made available in the future. These sensors can be added to the contestants’ submitted devices but will be evaluated and scored based on the realistic potential that they could be included in future, commercially available mobile devices. This evaluation and scoring will include criteria such as cost to implement, impact on form factor, ruggedness for use by law enforcement, and potential for technological advances on these sensors that will reduce cost and improve form factor. The intent is to retain the basic form factor of the mobile device so an officer does not need to carry a peripheral device.
Contestants may make small changes to the form factor of a mobile device to improve how the sensors function or add new functionality. An example of this type of change is a lens overlay that changes the functionality of the camera. Mobile device cases or skins that include such addon components are allowed. Any use of add-on components will be evaluated and scored based on the realistic potential that they could be attached or implemented on a mobile device. This evaluation and scoring will include criteria such as cost to implement, impact on form factor, ruggedness for use by law enforcement, and potential for technological advances on these NIST PSCR: mFIT Challenge, Official Rules Page 3 of 26 components that will reduce cost and improve form factor. The intent is to retain the basic form factor of the mobile device so an officer does not need to carry a peripheral device.
The following major issues, as cited in NIST.SP 500-334, should be considered for any contactless fingerprint capture technologies. Note that contactless capture is only one potential set of technologies appropriate for this challenge, and contact-based capture may also succeed in this challenge.