Standards and Academia

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International Center for Biometric Research

ICBR has been involved in standards development for over 14 years through committees like INCITS M1 and ISO/IEC JTC1 SC37. To provide students real-world experience, students participated on these committees by submitting documents, comments, and reviews. This engagement between academia and standards development benefits both fields by allowing applied research and education in new and emerging technical areas.

Technology

•ICBR (formerly BSPA Labs) has been involved
in standards for a number of years – over 14,
since the inception of INCITS M1, ISO/IEC
JTC1 SC37, and INCITS EB and subgroups
HISTORY

•Relatively new field, and a new lab, so we
wanted to communicate with industry and
government
•Students participated on these committees, by
submitting documents, comments, reviews
•Real world experience
MOTIVATION

APPLIED RESEARCH
The Interface between Research and Standardisation: Frictions and Possibilities
Knut Blinda, b, c *, Stephan Gaucha
14th EURAS workshop on standardisation
Cergy-Pontoise

•Education – classes
•Research – classes
•Research – new fields
•Engagement
INTERWOVEN STANDARDS AND
ACADEMIA

This research focused on classifying Human-Biometric Sensor Interaction errors in real-time. The Kinect 2 was used as a measuring device to track the position and movements of the subject through a simulated border control environment. Knowing, in detail, the state of the subject ensures that the human element of the HBSI model is analyzed accurately. A network connection was established with the iris device to know the state of the sensor and biometric system elements of the model. Information such as detection rate, extraction rate, quality, capture type, and more metrics was available for use in classifying HBSI errors. A Federal Inspection Station (FIS) booth was constructed to simulate a U.S. border control setting in an International airport. The subjects were taken through the process of capturing iris and fingerprint samples in an immigration setting. If errors occurred, the Kinect 2 program would classify the error and saved these for further analysis.

Interoperability and the Stability Score Index

International Center for Biometric Research

The stability score index, conceptualized in 2013, was designed to address the weaknesses of the zoo menagerie and other performance metrics by quantifying the relative stability of a user from on condition to another. In this paper, the measure of interoperability is the stability score from enrolling on one sensor and verifying on multiple sensors. The results showed that like performance, individual performance were not stable across these sensors. When examining stability by sensor family (capacitance, optical and thermal) we find that capacitive as the enrollment sensor were the least stable. Both enrolling and verifying on a thermal sensor, individuals were the most stable of the three family types. With respect to interaction type, enrolling on touch and verifying on swipe was more stable than enrolling on swipe and verifying on swipe, which was an interesting finding. Individuals using the thermal sensor generated the most stable stability scores.

Examining Intra-Visit Iris Stability - Visit 3

International Center for Biometric Research

Examining Intra-Visit Iris Stability - Visit 2

International Center for Biometric Research

Examining Intra-Visit Iris Stability - Visit 5

International Center for Biometric Research

The human signature provides a natural and publically-accepted legally-admissible method for providing authentication to a process. Automatic biometric signature systems assess both the drawn image and the temporal aspects of signature construction, providing enhanced verification rates over and above conventional outcome assessment. To enable the capture of these constructional data requires the use of specialist ‘tablet’ devices. In this paper we explore the enrolment performance using a range of common signature capture devices and investigate the reasons behind user preference. The results show that writing feedback and familiarity with conventional ‘paper and pen’ donation configurations are the primary motivation for user preference. These results inform the choice of signature device from both technical performance and user acceptance viewpoints.

Entropy of Fingerprints

International Center for Biometric Research

The inherent differences between secret-based authentication (such as passwords and PINs) and biometric authentication have left gaps in the credibility of biometrics. These gaps are due, in large part, to the inability to adequately cross-compare the two types of authentication. This paper provides a comparison between the two types of authentication by equating biometric entropy in the same way entropy of secrets are represented. Similar to the method used by Ratha, Connell, and Bolle [1], the x and y dimensions of the fingerprints were examined to determine all possible locations of minutiae. These locations were then examined based on the observed probability of minutiae occurring in each of the designated locations. The results of this work show statistically significant differences in the frequencies and probabilities of occurrence for minutiae location, type, and angle, across all possible minutiae locations. These components were applied to Shannon’s Information Theory [2] to determine the entropy of fingerprint biometrics, which was estimated to be equivalent to an 8.3-character, randomly chosen password

Biometric and usabilityInternational Center for Biometric Research

Examining Intra-Visit Iris Stability - Visit 1

International Center for Biometric Research

Best Practices in Reporting Time Duration in Biometrics

International Center for Biometric Research

A lot of work done in Center recently has focused around different topics concerning "time". Iris stability across different "times" has been in the forefront due to work in the undergraduate class, IT345, the graduate class IT545, as well as work in Ben Petry's thesis. Of course "time" is a fairly inaccurate word to use. Assessing stability over time is very ambiguous to the research question. For example time may mean millisecond, months, years, or even life of the user. Upon further examination of other academic literature, the reporting of research duration, collection interval, and specific time frame of interest are sporadic at best and missing completely at worst. To solve this issue, the Center has created the biometric duration scale (BDS) model with associated suggested best practices for reporting time duration in biometrics. The BDS model marries the general biometric model with HBSI model to create a logical flow of five phases: the presentation definition phase, sample phase, processing phase, and enrollment or matching phase. By tracking information through this progression such as specific subject presentations made, HBSI error, and FTE/Enrollment score (to name a few), performance within the general biometric model can be examined. The BDS model goes one step further by creating specific durations to report research specific metrics. By creating this model, outcomes that effect a yearly performance metrics can be looked at by examining monthly performance, daily performance, or even specific user presentations and how those subcomponents effect the whole system. Additionally, best practices for the reporting of duration is also included. The reporting methodology stems from ISO 8601 and is in compliance with ISO 21920. In the common reporting structure, start date, duration, number of visits at how many intervals, and time scope of interest for the specific research are given in a logical, readily available format along with the very specific, detailed ISO 8601 methodology. The goal of creating a formal script for reporting research duration was to eliminate ambiguity and create an environment where replication and drawing parallels between research is encouraged.

Advances in testing and evaluation using Human-Biometric sensor interaction m...

International Center for Biometric Research

Cerias talk on testing and evaluation

International Center for Biometric Research

IT 54500 overview

International Center for Biometric Research

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International Center for Biometric Research

(2010) Fingerprint recognition performance evaluation for mobile ID applications

International Center for Biometric Research

According to a report by Frost and Sullivan in 2007, revenues for non-AFIS fingerprint devices in notebook PC's and wireless devices is anticipated to grow from $148.5 million to $1588.0 million by 2014, a compound annual growth rate of 40.3% [1]. The AFIS market has a compound annual growth rate of 15.2% with revenues of $445.0 million in 2007. With the development of mobile applications in a number of different market segments, such as healthcare, retail, and law enforcement, this paper analyzed the performance of fingerprints of different sizes, from different sensors...

ICBR Databases

International Center for Biometric Research

Understanding Fingerprint Skin Characteristics and Image QualityInternational Center for Biometric Research

HBSI automation using the kinect

International Center for Biometric Research

(2013) Automatic Detection of Biometrics Transaction Times

International Center for Biometric Research

Presented at The 8th International Conference on Information Technology and Applications (ICITA 2013), Sydney Australia, July 1 - July 4 2013. The purpose of this paper is to illustrate the automatic detection of biometric transaction times using hand geometry as the modality of interest. Video recordings were segmented into individual frames and processed through a program to automatically detect interactions between the user and the system. Results include a mean enrollment time of 15.860 seconds and a mean verification time of 2.915 seconds.

Biometric Course Overview - Purdue ICBRInternational Center for Biometric Research

(2013) The Role of Test Administrator and Error

International Center for Biometric Research

Michael Brockly's M.S. thesis presentation for Purdue University, December 2013. This study created a framework to quantify and mitigate the amount of error that test administrators introduced to a biometric system during data collection. Prior research has focused only on the subject and the errors they make when interacting with biometric systems, while ignoring the test administrator. This study used a longitudinal data collection, focusing on demographics in government identification forms such as driver’s licenses, fingerprint metadata such a moisture and skin temperature, and face image compliance to an ISO best practice standard. Error was quantified from the first visit and baseline test administrator error rates were measured. Additional training, software development, and error mitigation techniques were introduced before a second visit, in which the error rates were measured again. The new system greatly reduced the amount of test administrator error and improved the integrity of the data collected. Findings from this study show how to measure test administrator error and how to reduce it in future data collections.

(2013) Examination of Stability in Fingerprint Recognition Across Force Levels

International Center for Biometric Research

(2011) The Impact of Force on Fingerprint Image Quality, Minutiae Count and P...

International Center for Biometric Research

The impact of force on acquiring a high quality fingerprint image has been systematically studied by researchers using single print optical scanners. A previous study examined force levels that ranged from 3N to 21N using a single print optical sensor. A second experiment used force levels ranging from 3N to 11N using a capacitive and optical single print sensor. Additional work has been conducted that looked at smaller increments of force also using an optical sensor. This paper contributes to the body of knowledge by using an alternative fingerprint sensor, an alternative force level and compares it to the auto-capture method.

(2007) Bacterial Survivability and Transferability on Biometric Devices

International Center for Biometric Research

The purpose of this study was to investigate bacterial recovery and transfer from three biometric sensors and the survivability of bacteria on the devices. The modalities tested were fingerprint, hand geometry and hand vein recognition, all of which require sensor contact with the hand or fingers to collect the biometric. Each sensor was tested separately with two species of bacteria, Staphylococcus aureus and Escherichia coli. Survivability was investigated by sterilizing the sensor surface, applying a known volume of diluted bacterial culture to the sensor and allowing it to dry. Bacteria were recovered at 5, 20, 40 and 60 minutes after drying by touching the contaminated device with a sterile finger cot. The finger cot was re-suspended in 5 mL of saline solution, and plated dilutions to obtain live cells counts from the bacterial recovery. The transferability of bacteria from each device surface was investigated by touching the contaminated device and then touching a plate to transfer the bacteria to growth medium to obtain live cell counts. The time lapse between consecutive touches was one minute, with the number of touches was n = 50. Again, S. aureus and E. coli were used separately as detection organisms. This paper will describe the results of the study in terms of survival curves and transfer curves of each bacterial strain for each device.

(2005) Implementation of Hand Geometry at Purdue University's Recreational Ce...

International Center for Biometric Research

This paper discusses the implementation issues of installing a commercially available hand geometry system in the current infrastructure of Purdue University's Recreational Sports Center. In addition to a performance analysis of the system, a pre- and post- data collection survey was distributed to the 129 test subjects gathering information on perceptions of biometrics, in particular hand geometry, as well as participants' thoughts and feelings during their interaction with the hand geometry device. The results of the survey suggest that participants were accepting of hand geometry. Additionally, analyses of the participants' survey responses revealed that 93% liked using hand geometry, 98% thought it was easy to use, and 87% preferred it to the existing card-based system, while nobody thought the device invaded their personal privacy. System performance achieved a 3-try match rate of 99.02% (FRR 0.98%) when "gaming"/potential impostor attempts were removed from analysis. The failure to enroll rate was zero. Statistical analyses exposed a significant difference in the scores of attempts made by users with prior hand geometry usage, and subjects that could not straighten out their hand on the device. However, there were no statistical difference in the effects of rings/no rings, improper hand placements/proper hand placements, or gender on hand geometry score.

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