1. Fingerprint Sensing Techniques, Devices and Applications
Rahul Singh
30th April 2003

2. Fingerprint Biometric
First used in China in 700 AD
Proposed in Europe in 1858, implemented in Germany in 1903.
Unique – So far no two prints from different fingers have been found that are identical

3. Fingerprint Biometric Characteristics
Fingerprint is the representation of the epidermis of a finger
Set of (almost/often) parallel ridge lines
Ridges produce local patterns
Source:

4. Fingerprint Biometric Characteristics
Five main classes of fingerprints
Arch
Tented Arch
Left Loop
Right Loop
Whorl
Source:

5. Fingerprint Sensing Two stages Capture Fingerprint image
Process image and extract features
Store data for comparison or compare with stored templates

6. Types of Fingerprint Sensors
Optic Reflexive
Finger lies on a prism. Total internal reflection produces image of fingerprint on a camera chip
Optic Transmissive with Fiber Optic Plate
Light source illuminates through the finger
Finger lies on fiber-optic plate that transmits image data to camera chip
Optical Line
Pixel array measures the light reflected by the finger
Source:

7. Types of Fingerprint Sensors
Capacitive Line
Capacitor array measures the capacitance at each pixel
Thermal Line
Finger is moved across a narrow array of thermal sensors
Temperature varies across the grooves and ridges
Thermal sensors measure the temperature differences over time
Pressure Sensitive
Sensor measures the pressure per pixel
Dynamic Capacitive
Capacitance is measured by A/C voltage
Source:

8. Types of Fingerprint Sensors
Static Capacitive Type 1
One electrode per pixel
Capacitance measured w.r.t neighboring pixel.
If pixel is on a groove capacitance is small
If pixel is on a ridge then capacitance is large
Static Capacitive Type 2
Same as above except capacitance is measure w.r.t ground
Acoustic (Ultrasound)
Image of fingerprint is recorded by very high frequency sound
Source:

9. Capacitive Sensing
Fingerprint consists of tightly spaced ridges and valleys
Sensor consists of a capacitive array
Capacitive array acts as one plate of a capacitor while the finger acts as the other
Each pixel in the array is charged to a reference voltage and allowed to discharge with a reference current
The rate of change of potential at each pixel is proportional to the capacitance seen by the array

10. Capacitive Sensing Charge amp reset. Inverter O/P settles to threshold
Ref. charge applied to I/P
O/P Voltage proportional to feedback capacitance
Inverter O/P = upper saturation level if there is no feedback capacitance
Inverter O/P = close to logical threshold when feedback capacitance is large
Source:

11. Capacitive Sensing 300 x 300 pixel array (90,000 pixels)
500 dpi Fingerprint image
Source:

12. Optical Sensing Finger touches light emitting TactileSense polymer
Hello1
Hello2
Finger touches light emitting TactileSense polymer
Photodiode array embedded in the glass detects illumination
Image is captured and transferred for storage
Source: [Tactilesense]

13. Optical Sensing
Sensing by projecting an image of the fingerprint onto a camera by total internal reflection.
Source:

14. Optical Vs Capacitive Capacitive Optical Sensors
Greater miniaturization
Newer technology
Can be embedded into small devices
Prone to dirt etc since finger touches silicon
Relatively cheap
Optical Sensors
Larger sensing area since manufacturing large pure silicon chips is expensive
More robust. Longer life
More expensive
Better image quality and higher resolution

15. Factors affecting the scan
Image quality
Sharpness
Contrast
Distortion
Source:

16. Factors affecting the scan
Resolution – higher is better
Too low and we cannot detect the minutiae
Sensing area
Average fingerprint is about 0.5” x 0.7”
Large area (1.0” x 1.0”) ensures that overlap effects (leading to false rejections) are reduced
Source:

17. Data Storage and Matching
Minutiae or Galton Characteristics
Termination of Ridge lines
Bifurcation of Ridge lines
Source:

18. Data Storage and Matching
Final data size = 300 to 600 bytes
Source:

19. Data Storage and Matching
Directional Map
Discrete matrix whose elements denote the orientation of the tangent to ridge lines

20. FX2000 FX2000 – Optical Sensor Database of 100 users (non-experts)
Low quality fingerprints
Efficiency
TASK
SPEED_DEFAULT
SPEED_FAST
Feature extraction
350 ms
260 ms
Matching
120 ms
47 ms
Identity verification (1:1)
470 ms
307 ms
Identification (1:50)
3.35 sec
1.43 sec
Accuracy
Verification time (1:1)
Time to verify the identity
Identification time (1:50)
Average time to identify an individual. 50 Users. Match is found in the middle.
threshold t
SPEED_DEFAULT
SPEED_FAST
FAR
FRR
0.3500
(0.49%)
(0.05%)
(0.32%)
(0.09%)
0.3750
(0.25%)
(0.10%)
(0.14%)
0.4000
(0.11%)
(0.20%)
0.4250
(0.06%)
(0.19%)
(0.02%)
(0.34%)
0.4500
(0.04%)
(0.26%)
(0.00%)
0.4750
(0.36%)
(0.63%)

21. Secugen FDA01/FCA01 Optical sensor Resolution = 500 dpi
Verification time = < 1 second
Sensing area = 13.6mm x 16.2mm

22. Authentec FingerLoc AF-S2 AFS8500 Capacitive 68 pin PLCC
Resolution: 250 dpi
Array size: .512”x.512”
AFS8500
144 pin LQFP
Array Size: .384” x .384”

23. Biomouse/Biomouse plus
Optical sensor
“High speed” matching algorithm – 400 prints per second on pII 400.
Resolution = 500 dpi
Average template size = 350 bytes
Biomouse Plus comes with built in smart card reader

24. Defeating Fingerprint Scanners
Gummi bears defeat fingerprint sensors
Japanese cryptographer
Gelatin + plastic mould
Latent fingerprints from glass
Cyanoacrylate Adhesive (superglue fules)
Digital camera
Adobe Photoshop
Photosensitive PCB – etched print in copper
Moulded finger with print
Source:

25. Defeating Fingerprint Sensors
More sophisticated devices use incorporate biosensing modules prior to fingerprint capture
Detect blood flow
Detect body heat
Sensor shuts down if no life is detected

26. Types of attack Brute force Latent print Replay Trojan Horses
Fake feature
Dead feature
Other (software leaks, bad security policies etc)

27. Applications Secure logins via keyboard modules
User identification at kiosks
Biometric door locks
Credit card security
Weapon activation
Theft protection

28. Fingerprint Verification for Smart Cards Motorola, Australia
Senior Honors thesis
Develop biometric security solution (prototype) for Motorola dual-slot phones
Users insert credit card into slot 1 for e-commerce
Smart card with embedded biometric into slot 2
Fingerprint sensor on phone identifies user and authorizes use of credit card

29. Fingerprint Verification for Smart Cards Motorola, Australia
Enrollment
Fingerprint template
X.509 Certificate
Smart Card
Fingerprint template
X.509 Certificate

30. Fingerprint Verification for Smart Cards Motorola, Australia
Fingerprint template
Compare
Smart Card
Fingerprint template
X.509 Certificate
Fingerprint template
X.509 Certificate
Fingerprint template

31. Questions ?