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A Quantitative Analysis Study on the Effects of Moisture and Light Source on FTIR Fingerprint Image Qualityopen access

Authors
Shin, ManjaeLee, SeungbongBaek, SeungbinLee, SunghoonKim, Sungmin
Issue Date
Feb-2025
Publisher
MDPI
Keywords
biometric; fingerprint; frustrated total internal reflection (FTIR); clinical study; statistical analysis
Citation
Sensors, v.25, no.4, pp 1 - 21
Pages
21
Indexed
SCIE
SCOPUS
Journal Title
Sensors
Volume
25
Number
4
Start Page
1
End Page
21
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/57949
DOI
10.3390/s25041276
ISSN
1424-8220
1424-8220
Abstract
The frustrated total internal reflection (FTIR) optical fingerprint scanning method is widely used due to its cost-effectiveness. However, fingerprint image quality is highly dependent on fingertip surface conditions, with moisture generally considered a degrading factor. Interestingly, a prior study reported that excessive moisture may improve image quality, though their findings were based on qualitative observations, necessitating further quantitative analysis. Additionally, since the FTIR method relies on optical principles, image quality is also influenced by the wavelength of the light source. In this study, we conducted a preliminary clinical experiment to quantitatively analyze the impact of moisture levels on fingertips (wet, dry, and control) and light wavelengths (red, green, and blue) on FTIR fingerprint image quality. A total of 20 male and female participants with no physical impairments were involved. The results suggest that FTIR fingerprint image quality may improve under wet conditions and when illuminated with green and blue light sources compared to dry conditions and red light. Statistical evidence supports this consistent trend. However, given the limited sample size, the statistical validity and generalizability of these findings should be interpreted with caution. These insights provide a basis for optimizing fingerprint imaging conditions, potentially enhancing the reliability and accuracy of automatic fingerprint identification systems (AFIS) by reducing variations in individual fingerprint quality.
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