Fingerprint skin moisture impact on biometric performance

Olsen, Martin Aastrup; Dusio, Marek; Busch, Christoph

doi:10.1109/iwbf.2015.7110223

Cited by 15 publications

(11 citation statements)

References 11 publications

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“…Although the amount of moisture on users' fingers has an impact on overall biometric performance [114], the effects of humidity on the survival of microorganisms on environmental surfaces such as fingerprint scanners vary greatly between different classes of microorganisms and are significantly influenced by the presence of a cell wall or protective membrane.…”

Section: Relative Humidity Temperature and Biofilm Formationmentioning

confidence: 99%

Fingerprint Biometric System Hygiene and the Risk of COVID-19 Transmission

Okereafor¹,

Ekong²,

Markson³

et al. 2020

JMIR Biomed Eng

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Biometric systems use scanners to verify the identity of human beings by measuring the patterns of their behavioral or physiological characteristics. Some biometric systems are contactless and do not require direct touch to perform these measurements; others, such as fingerprint verification systems, require the user to make direct physical contact with the scanner for a specified duration for the biometric pattern of the user to be properly read and measured. This may increase the possibility of contamination with harmful microbial pathogens or of cross-contamination of food and water by subsequent users. Physical contact also increases the likelihood of inoculation of harmful microbial pathogens into the respiratory tract, thereby triggering infectious diseases. In this viewpoint, we establish the likelihood of infectious disease transmission through touch-based fingerprint biometric devices and discuss control measures to curb the spread of infectious diseases, including COVID-19.

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Section: Relative Humidity Temperature and Biofilm Formationmentioning

confidence: 99%

Fingerprint Biometric System Hygiene and the Risk of COVID-19 Transmission

Okereafor¹,

Ekong²,

Markson³

et al. 2020

JMIR Biomed Eng

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“…The fact that quality of the fingerprint impacts biometric system performance was recognized by Olsen et al [9]. In their research, the authors collected database of 6600 fingerprints collected from 33 persons, by the use of five different optical fingerprint sensors.…”

Section: Fingerprint Acquisitionmentioning

confidence: 99%

Bringing Biometric Sensors to the Classroom: A Fingerprint Acquisition Laboratory for Improving Student Motivation and Commitment

et al. 2020

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This paper presents a research study conducted in a specially developed laboratory for biometric engineering education. The laboratory gives students an opportunity to learn more about fingerprint acquisition and analyze the impact of acquisition on other parts of the biometric authentication process. An IoT approach was used, as different types of sensors (biometric sensors, thermometer, and humidity sensor) and components (heaters and workstations) were included in setting up a working surface for biometric data acquisition. Working surfaces create a network where data collected from each working station is recorded in a database. In parallel with biometric data acquisition, environmental condition parameters are recorded. Collected data is available to students for later analysis through the use of a specially developed visualization tool. In order to fully utilize the possibilities the laboratory provides, a flipped classroom approach was used. An evaluation study was done as a part of the course of Biometric technology held at the University of Belgrade. Research results show improvements in student learning outcomes and motivation.

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“…Table 1 shows the calculation results for several different cases where the sensor patterns are composed of different numbers of arrays, while the fingerprint sensing pixel pitches are in the reasonable range of 70-85 μm, which correspond to resolutions of 300-363 dpi. Fingerprint images in this resolution range can be effectively used in commercial devices employing a pattern-based matching algorithm 12,21 . The difference between C M-R and C M-V , denoted ΔC M , is shown in the table instead of the capacitance values because the amplitude of the sensor output signal is determined by ΔC M .…”

Section: Projected Fieldsmentioning

confidence: 99%

“…However, in some cases, these sensors may not work as satisfactorily as conventional fingerprint sensors. The optical underdisplay fingerprint sensor, which recognizes a fingerprint using the difference in light reflected at the finger ridge and valley areas, has an issue in recognizing dry fingers, which cannot make uniform and consistent contact with the surface of the sensor cover layer 12,13 . This issue arises because the sensor may identify a finger ridge area, which is not making good surface contact, as a valley area since part of the light will be reflected at the cover surface instead of propagating through the finger on the surface.…”

Section: Introductionmentioning

confidence: 99%

On-screen fingerprint sensor with optically and electrically tailored transparent electrode patterns for use on high-resolution mobile displays

et al. 2020

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In this study, a mutual capacitive-type on-screen fingerprint sensor, which can recognize fingerprints on a display screen to provide smartphones with full-screen displays with a minimal bezel area, is fabricated. On-screen fingerprint sensors are fabricated using an indium tin oxide transparent conductor with a sheet resistance of ~10 Ω/sq. and a transmittance of ~94% (~86% with the substrate effect) in the visible wavelength range, and assembled onto a display panel. Even at this high transmittance, the electrodes can degrade the display quality when they are placed on the display. The interference between periodic display pixel arrays and sensor patterns can lead to the Moiré phenomenon. It is necessary to find an appropriate sensor pattern that minimizes the Moiré pattern, while maintaining the signal sensitivity. To search for appropriate patterns, a numerical calculation is carried out over wide ranges of pitches and rotation angles. The range is narrowed for an experimental evaluation, which is used to finally determine the sensor design. As the selected sensor pitches are too small to detect capacitance variations, three unit patterns are electrically connected to obtain a unit block generating a larger signal. By applying the selected sensor pattern and circuit driving by block, fingerprint sensing on a display is demonstrated with a prototype built on a commercial smartphone.

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Fingerprint skin moisture impact on biometric performance

Cited by 15 publications

References 11 publications

Fingerprint Biometric System Hygiene and the Risk of COVID-19 Transmission

Fingerprint Biometric System Hygiene and the Risk of COVID-19 Transmission

Bringing Biometric Sensors to the Classroom: A Fingerprint Acquisition Laboratory for Improving Student Motivation and Commitment

On-screen fingerprint sensor with optically and electrically tailored transparent electrode patterns for use on high-resolution mobile displays

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