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![(a) Construction of a novel fingerprint sensor using scattered transmission light. (b) Normal fingerprint and the OCT images. (c) Fingerprint images of a wrinkled finger and the OCT image. (d) Almost flat finger image and the optical coherence tomography (OTC) image [89]. (e) Construction of equipment, (f) structure of subsurface fingerprints, (g) different layers of subsurface fingerprint, and (g-k) different fingerprint images. The images from left to right correspond to the cornea, internal, papillary, fusion, and traditional 2D fingerprints [159].](publication/371628787/figure/fig4/AS:11431281168448245@1686971762123/a-Construction-of-a-novel-fingerprint-sensor-using-scattered-transmission-light-b.png)
(a) Construction of a novel fingerprint sensor using scattered transmission light. (b) Normal fingerprint and the OCT images. (c) Fingerprint images of a wrinkled finger and the OCT image. (d) Almost flat finger image and the optical coherence tomography (OTC) image [89]. (e) Construction of equipment, (f) structure of subsurface fingerprints, (g) different layers of subsurface fingerprint, and (g-k) different fingerprint images. The images from left to right correspond to the cornea, internal, papillary, fusion, and traditional 2D fingerprints [159].
Source publication
Identification technology based on biometrics is a branch of research that employs the unique individual traits of humans to authenticate identity, which is the most secure method of identification based on its exceptional high dependability and stability of human biometrics. Common biometric identifiers include fingerprints, irises, and facial sou...
Contexts in source publication
Context 1
... 121-156 µm images are the ridges of the internal fingerprints, whilst the 191-210 µm depth images are the valleys, allowing fingerprint pictures to be produced [158]. Figure 7 shows a scanning picture of common fingerprints, moist fingerprints, and fingerprints based on an optical coherence layer. ...
Context 2
... [159] suggested the optical coherence tomography (OCT)-based fingerprint identification system shown in Figure 7e-g. This device's SD-OCT approach utilizes a light source centered at 840 nm; the light source light is generated by a super light emitting diode (SLED), and two identical telephoto lenses serve as a focusing lens and a scanning lens, respectively [160]. ...
Context 3
... 121-156 µm images are the ridges of the internal fingerprints, whilst the 191-210 µm depth images are the valleys, allowing fingerprint pictures to be produced [158]. Figure 7 shows a scanning picture of common fingerprints, moist fingerprints, and fingerprints based on an optical coherence layer. ...
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Citations
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Biometric fingerprint identification hinges on the reliability of its sensors; however, calibrating and standardizing these sensors poses significant challenges, particularly in regards to repeatability and data diversity. To tackle these issues, we propose methodologies for fabricating synthetic 3D fingerprint targets, or phantoms, that closely emulate real human fingerprints. These phantoms enable the precise evaluation and validation of fingerprint sensors under controlled and repeatable conditions. Our research employs laser engraving, 3D printing, and CNC machining techniques, utilizing different materials. We assess the phantoms’ fidelity to synthetic fingerprint patterns, intra-class variability, and interoperability across different manufacturing methods. The findings demonstrate that a combination of laser engraving or CNC machining with silicone casting produces finger-like phantoms with high accuracy and consistency for rolled fingerprint recordings. For slap recordings, direct laser engraving of flat silicone targets excels, and in the contactless fingerprint sensor setting, 3D printing and silicone filling provide the most favorable attributes. Our work enables a comprehensive, method-independent comparison of various fabrication methodologies, offering a unique perspective on the strengths and weaknesses of each approach. This facilitates a broader understanding of fingerprint recognition system validation and performance assessment.
