Toward Synthetic Physical Fingerprint Targets
<p>Synthetic fingerprint generation with SFinGe output (<b>a</b>), applied Gabor filter (<b>b</b>), applied thresholding algorithm (<b>c</b>), and finally, path traced and converted to a vector graphic (<b>d</b>).</p> "> Figure 2
<p>Laser-engraved elastomer targets. (<b>a</b>) Laser-engraved elastomer stripes. Stripe with 0.95 mm thickness on top, stripe with 1.42 mm thickness below. (<b>b</b>) Exemplary elastomer stripes applied to the wooden target holder.</p> "> Figure 3
<p>Silicone plates used for laser engraving. (<b>a</b>) Silicone plate from the company Gospire used as a training skin for tattoo artists. (<b>b</b>) Silicone plate created in-house with Dragon Skin 10 Fast.</p> "> Figure 4
<p>Aluminum half pipe mold. (<b>a</b>) Aluminum half-pipe mold with laser engraving. (<b>b</b>) Plug for filling the mold with silicone.</p> "> Figure 5
<p>Resin-printed mold halves. (<b>a</b>) Printed using the ES2 Elegoo Saturn 2-8K resin printer. (<b>b</b>) Printed using the Alpine3D GmbH SLA service.</p> "> Figure 6
<p>Silicone target made from 3D-printed resin mold.</p> "> Figure 7
<p>CNC-machined master targets.</p> "> Figure 8
<p>Synthetic fingerprint results used for the following: laser-engraved elastomer samples (<b>a</b>), both laser-engraved silicone samples and the laser-engraved aluminum half-pipe mold (<b>b</b>), and the first version of the 3D-printed resin mold (<b>c</b>).</p> "> Figure 9
<p>Upsampling of synthetic fingerprint image used for 3D-printed second-generation resin mold.</p> "> Figure 10
<p>Laser-engraved phantoms (<b>b</b>–<b>e</b>) and mold (<b>a</b>). Phantom (<b>b</b>) is the silicone filling of the aluminum mold (<b>a</b>), and the other images are direct laser engraving on elastomer (<b>c</b>) and silicone (<b>d</b>,<b>e</b>).</p> "> Figure 11
<p>The figure shows the top-down view on the synthetic fingerprint engraved in the elastomer with the corresponding color coded height profile. Scale bar 5 mm.</p> "> Figure 12
<p>The figure shows the top-down view on the checkerboard structure engraved in the elastomer with the corresponding height profile color coded. The yellow/magenta line highlights the area of the height profile in the bottom plot, while the read dashed line indicates the same area in the height map. Within the plot, the increasing and decreasing shoulder and the upper and lower plateau of the structure were selected by hand. Scale bar 5 mm.</p> "> Figure 13
<p>Top-down capture of the Gospire silicone plate. The cyan/yellow line in the upper left image highlights the area where the height profile is measured and the red line the corresponding area in the height map. Scale bar 5 mm.</p> "> Figure 14
<p>Top-down capture of the in-house created Dragon Skin 10 Fast silicone plate. The cyan/yellow line in the upper left image highlights the area where the height profile is measured and the red line the corresponding area in the height map. Scale bar 5 mm.</p> "> Figure 15
<p>Top-down capture of an in-house Dragon Skin 10 Fast synthetic fingerprint sample created by casting the silicone in an aluminum half-pipe with laser-engraved fingerprint structure. The cyan/yellow line in the upper left image highlights the area where the height profile is measured and the red line the corresponding area in the height map. Scale bar 5 mm.</p> "> Figure 16
<p>3D-printed resin molds and fingerprint phantoms. Created with the ES2 Elegoo Saturn 2-8K resin printer (ES2) or the Alpine3D GmbH SLA service (ALP).</p> "> Figure 17
<p>Top-down captures of created Gelafix-based fingerprint targets on different days. From <b>left</b> to <b>right</b>, day 0, day 1, day 4, and after approximately 6 months. The corresponding diameters of the fitted cylinders are summarized in <a href="#sensors-24-02847-t002" class="html-table">Table 2</a>. Scale bar 5 mm.</p> "> Figure 18
<p>Top-down capture of a fresh Gelafix sample created using the in-house ES2 Elegoo Saturn 2-8K resin printer. The yellow/purple line highlights the area selected for measuring the height profile, which can be seen in the height profile via the dashed red line.</p> "> Figure 19
<p>Top-down capture of an approximate 6-month-old Gelafix sample created using the in-house ES2 Elegoo Saturn 2-8K resin printer. The cyan/yellow line, which can be seen in the height profile via the dashed red line. highlights the area selected for measuring the height profile.</p> "> Figure 20
<p>Finger phantom cast with Dragon Skin 10, while using the 3D resin-printed mold by Alpine 3D. The yellow/purple line highlights the area selected for measuring the height profile, which can be seen in the height profile via the dashed red line.</p> "> Figure 21
<p>Fingerprint phantoms made from CNC-machined aluminum master targets.</p> "> Figure 22
<p>Top-down captures of the Dragon Skin 10 Fast-based fingerprint targets with a concentric Ronchi pattern created from the CNC-machined aluminum master target. Along the yellow/cyan line, the height profile is measured, which can be seen in the height profile via the dashed red line.</p> "> Figure 23
<p>Dragon Skin 10 Fast-based fingerprint targets with a synthetic fingerprint created via a negative mold taken from the aluminum milled master targets. The height profile along the cyan/yellow line is taken to measure the ridge line depth and width, which can be seen in the height profile via the dashed red line.</p> ">
Abstract
:1. Introduction
1.1. Related Work
1.1.1. Synthetic Fingerprint Generation
1.1.2. Physical Fingerprint Generation
2. Methods—Generating Synthetic Fingerprints
3. Methods—Generating Synthetic 3D Targets
3.1. Laser Engraving
3.1.1. Elastomer Target
3.1.2. Silicone Target
3.1.3. Aluminum Half-Pipe Mold
3.2. 3D Printing of the Resin Mold
3.2.1. Filling—Kryolan Gelafix
3.2.2. Filling—Silicone
3.3. CNC Machining of the Aluminum Master Target and Filling
3.3.1. Milling the Aluminum Master
3.3.2. Surface Enhancement through Sandblasting
3.3.3. Creation of a Negative with Silicone
3.3.4. Creation of a Positive with Silicone
4. Methods—Measuring Devices
4.1. Profilometer
4.1.1. Image Processing Workflow
- compensation of the general sample tilt
- compensation of the sample waviness, e.g., originating from the gluing step, especially for the flat samples or take the geometry of the sample into account, e.g., unwrap/unroll the cylindrical fingerprint target
- definition of the reference height for relative height measurements
Elastomer Targets
Silicone Plate Targets
Finger-Like Targets
4.2. Greenbit Dactyscan 84c
4.3. Microscope
5. Methods—Measuring Algorithms
5.1. NFIQ 2 Analysis of Phantoms and Synthetic Fingerprints
5.2. End-to-End Fidelity
5.2.1. Scale Pre-Processing
5.2.2. Matcher Comparison
5.3. Intra-Class Variability of 3D Target Impressions
6. Results—Generating Synthetic Fingerprints
7. Results—Generating 3D Targets
7.1. Laser Engraving
7.1.1. Elastomer Target
7.1.2. Silicone Target
7.1.3. Aluminum Half-Pipe Mold
7.2. 3D Printing of Resin Mold
7.2.1. Gelafix Filling
7.2.2. Silicone Filling
7.3. CNC Machining of Aluminum Master Target and Filling
7.4. Overview
8. Results—Fidelity of 3D Targets
8.1. NFIQ 2 Analysis of Phantoms and Synthetic Fingerprints
8.2. End-to-End Fidelity
8.2.1. Pre-Processing
8.2.2. Matcher Comparison
8.3. Intra-Class Variability of the 3D Target Impressions
9. Discussion
9.1. Applicability
- Test Targets with Ground Truth: Synthetic fingerprint targets, based on digital 3D models, inherently possess a ground truth. Therefore, they serve as valuable tools for testing the accuracy and efficacy of fingerprint scanners in reconstructing this ground truth and furthermore can act as targets in the standardization of fingerprint sensors [67].
- Data Protection-Compliant Fingerprint Samples: In many countries, strict regulations govern the use of person-related fingerprints [68,69,70]. Synthetic prints provide a solution to circumvent these data protection regulations, enabling for example the publication of fingerprint images without compromising individual privacy.
- Quality Control: Synthetic fingerprint targets are instrumental in manufacturing processes to ensure the precision and consistency of fingerprint sensors and biometric devices before deployment in real-world scenarios [35]. They facilitate rigorous quality control measures, thereby enhancing the reliability of these devices.
- Training Humans: Synthetic fingerprint targets are valuable for training operators of forensic fingerprint scanners, particularly for rolled fingerprint captures [71,72,73]. These targets provide physical support and enable hands-on training, ensuring that personnel are adequately trained to handle real-world scenarios effectively.
- Artificial Intelligence: Synthetic fingerprints can play a pivotal role in training machine learning models for fingerprint recognition algorithms [74,75,76,77,78]. By providing diverse and controlled datasets, synthetic fingerprints contribute to the development of more robust and accurate AI systems for biometric security applications.
- Presentation Attack: Synthetic fingerprints can also be utilized in simulating presentation attacks, where artificial replicas are employed to assess the vulnerability of fingerprint recognition systems to spoofing attempts [40,79,80]. This allows for the evaluation and enhancement of system security against potential threats.
9.2. Generating 3D Targets
9.3. Fidelity of 3D Targets
9.4. Overview
10. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
PIV | Personal Identity Verification |
NIST | National Institute of Standards and Technology |
PAD | Presentation Attack Detection |
PAIs | Presentation Attack Instruments |
SFinGe | Synthetic Fingerprint Generator |
DPI | Dots-per-Inch |
MSLA | Masked Stereolithography |
SLA | Stereolithography |
FTIR | Frustrated total internal reflection |
NFIQ 2 | NIST Finger Image Quality version 2 |
NBIS | NIST Biometric Image Software |
ES2 | ES2 Elegoo Saturn 2-8k resin printer |
ALP | Alpine3D GmbH |
BSI | Federal Office for Information Security |
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Dragon Skin 10 Fast [44] | Dragon Skin 20 [44] | Human Skin | |
---|---|---|---|
Density [kg/m3] | 1070 | 1080 | 1250 [45] |
Pot Life [min.] | 8 | 25 | - |
Cure Time | 75 min | 4 h | - |
Hardness [Shore A] | 10 | 20 | 20–41 [46,47] |
Shrinkage [m/m] | <0.001 | <0.001 | - |
Age | Measured Cylindrical Diameter in mm | Shrinkage in % |
---|---|---|
Day 0 | 19.29 | |
Day 1 | 17.61 | 8.71 |
Day 4 | 16.36 | 15.19 |
>6 Months | 15.97 | 17.22 |
Methodology | Price | Manual Labor | Artifacts | Valley Width [µm] | Ridge Depth [µm] |
---|---|---|---|---|---|
CNC Alum | setup + ≈1000€ | High | Minimal | ||
Laser Alum HP Silicone | ≈8000€ + 1000€ | Medium | Offset of ridge lines | ||
Laser Elastomer | ≈200€ | Low | Varying ridge thickness | ||
Laser Silicone Gospire | ≈200€ | Low | Minimal | ||
Laser Silicone In-house | ≈200€ | Medium | Small offset of ridge lines | ||
Print ES2 Gelafix | ≈400€ + <10€ | Medium | Air bubbles in phantom and small holes in mold | ||
Print ES2 Silicone | ≈400€ + <5€ | Medium | Small holes in mold | 370 | 128 |
Print ALP Silicone | ≈3000€ + 50€ | Medium | Minimal |
Methodology | 2D Synth | Phantom |
---|---|---|
CNC Alum | 56 | 53 |
Laser Alum HP Silicone | 44 | 52 |
Laser Elastomer | 53 | 61 |
Laser Silicone Gospire | 44 | 47 |
Laser Silicone Inouse | 44 | 42 |
Print ES2 Gelafix | 56 | 36 |
Print ES2 Silicone | 56 | 37 |
Print Alpine Silicone | 54 | 50 |
-Arch | 53 | 54 |
-Tented Arch | 54 | 55 |
-Left Loop | 59 | 50 |
-Right Loop | 57 | 52 |
-Whorl | 46 | 40 |
Methodology | x | y | |
---|---|---|---|
CNC Alum | 0.57 | 0.58 | 0.0 |
Laser Alum HP Silicone | 0.91 | 1.03 | 0.0 |
Laser Elastomer | 0.99 | 1.02 | 8.3 |
Laser Silicone Gospire | 0.93 | 1.04 | 0.0 |
Laser Silicone Inouse | 0.86 | 1.00 | 0.0 |
Print ES2 Gelafix | 0.79 | 0.83 | 13.9 |
Print ES2 Silicone | 0.68 | 0.80 | 13.7 |
Print Alpine Silicone | 0.64 | 0.88 | 20.7 |
Methodology | Avg | Idkit | Nbis | FinSource |
---|---|---|---|---|
CNC Alum | 481 | 1000 | 158 | 285 |
Laser Alum HP Silicone | 593 | 1000 | 104 | 674 |
Laser Elastomer 1 | 93 | 112 | 44 | 123 |
Laser Silicone Gospire | 771 | 1000 | 186 | 1126 |
Laser Silicone In-house | 689 | 1000 | 158 | 908 |
Print ES2 Gelafix 2 | 275 | 570 | 54 | 201 |
Print ES2 Silicone 2 | 295 | 615 | 70 | 200 |
Print ALP Silicone 2 | 388 | 829 | 92 | 243 |
-Arch | 421 | 904 | 53 | 304 |
-Tented Arch | 373 | 803 | 71 | 245 |
-Left Loop | 465 | 977 | 130 | 289 |
-Right Loop | 430 | 906 | 137 | 246 |
-Whorl | 252 | 553 | 72 | 132 |
Methodology | Avg | Idkit | Nbis | FinSource |
---|---|---|---|---|
CNC Alum | 569 | 1000 | 277 | 429 |
Laser Alum HP Silicone | 624 | 1000 | 127 | 745 |
Laser Elastomer 1 | 537 | 778 | 207 | 625 |
Print ES2 Gelafix 2 | 363 | 727 | 123 | 238 |
Print ES2 Silicone 2 | 514 | 954 | 190 | 408 |
Print ALP Silicone 2 | 538 | 985 | 173 | 457 |
-Arch | 545 | 1000 | 145 | 491 |
-Tented Arch | 518 | 991 | 147 | 416 |
-Left Loop | 561 | 1000 | 210 | 474 |
-Right Loop | 509 | 959 | 177 | 392 |
-Whorl | 557 | 974 | 186 | 512 |
Methodology | Avg | Idkit | Nbis | FinSource |
---|---|---|---|---|
Laser Alum HP Silicone, Laser Silicone Gospire, Laser Silicone In-house | 575 | 966 | 99 | 660 |
Laser Alum HP Silicone, Laser Silicone Gospire | 608 | 1000 | 119 | 705 |
Laser Alum HP Silicone, Laser Silicone In-house | 560 | 956 | 93 | 630 |
Laser Silicone Gospire, Laser Silicone In-house | 661 | 978 | 125 | 880 |
Print ES2 Silicone, Print ES2 Gelafix, CNC Alum | 357 | 708 | 103 | 260 |
Print ES2 Gelafix, CNC Alum | 343 | 679 | 106 | 244 |
Print ES2 Silicone, CNC Alum | 411 | 770 | 135 | 327 |
Print ES2 Silicone, Print ES2 Gelafix | 383 | 764 | 118 | 267 |
Price | Labor | Fidelity | Interop. | R. Form | R. Consistency | Artifacts | Geometry | Longevity | |
---|---|---|---|---|---|---|---|---|---|
Laser Elastomer | ↓ | ↓ | ⇊ | ↑ | Wide | ˷ | Minor | Flat | ↑ |
Laser Silicone | ↓ | ↓ | ⇈ | ↑ | Wide | ↑ | Minimal | Flat | ↑ |
Laser Alum. HP | ↑ | ˷ | ↑ | ↑ | Wide | ˷ | Major | Cylindrical | ↑ |
3D Print Gelafix | ˷ | ˷ | ↓ | ˷ | Slim | ˷ | Major | Cylindrical + Tip | ↓ |
3D Print Silicone | ˷ | ˷ | ˷ | ↑ | Slim | ˷ | Minimal | Cylindrical + Tip | ↑ |
CNC Alum. Silicone | ↑ | ↑ | ↑ | ↑ | Slim | ↑ | Minimal | Cylindrical | ↑ |
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Ruzicka, L.; Strobl, B.; Bergmann, S.; Nolden, G.; Michalsky, T.; Domscheit, C.; Priesnitz, J.; Blümel, F.; Kohn, B.; Heitzinger, C. Toward Synthetic Physical Fingerprint Targets. Sensors 2024, 24, 2847. https://doi.org/10.3390/s24092847
Ruzicka L, Strobl B, Bergmann S, Nolden G, Michalsky T, Domscheit C, Priesnitz J, Blümel F, Kohn B, Heitzinger C. Toward Synthetic Physical Fingerprint Targets. Sensors. 2024; 24(9):2847. https://doi.org/10.3390/s24092847
Chicago/Turabian StyleRuzicka, Laurenz, Bernhard Strobl, Stephan Bergmann, Gerd Nolden, Tom Michalsky, Christoph Domscheit, Jannis Priesnitz, Florian Blümel, Bernhard Kohn, and Clemens Heitzinger. 2024. "Toward Synthetic Physical Fingerprint Targets" Sensors 24, no. 9: 2847. https://doi.org/10.3390/s24092847