These slides use concepts from my (Jeff Funk) course entitled analyzing hi-tech opportunities to show how the cost and performance of biometrics are improving rapidly, making many new applications possible, particularly for fingerprinting in phones. Improvements in cameras and other electronics are making optical, capacitive, and ultrasound sensors better. Improvements in microprocessors are making the matching algorithms operate faster and with higher accuracy. We expect biometrics to become widely used in the next few years beginning with smart phones and followed by automobiles, homes, and offices. Better biometrics in smart phones will promote security and mobile commerce.

1. Biometric Technology
-- Finger Print Business Opportunity
Team Members:
YANG QIAN A0147178W
LIM KIM CHYE A0147179U
QUEK YONG GUAN A0147276X
SONG ZHIWEI A0026195E For information on other technologies see
http://www.slideshare.net/Funk98/presentations

2. 2
Technology Overview
Applications
PerformanceHardware/Software
Cost Analysis
Entrepreneur
Opportunity
Recommendation SystemFinger Print Technology

3. 3
• A biometric identification system provides an automated method
of recognizing an individual based on their unique physiological
characteristics
 Metrics related to human characteristics
 These metrics are Distinctive and Measurable (label
and describe individuals)
What is Biometric?

4. 4
Why Biometric?
• Traditional, security is by what we:
–Know (PIN, Password)
–Have (Key, smart card)
• Both of these security measures can be hacked, stolen, forgotten,
duplicated and have too many.
• Modern, security is by we:
–Are (Body)
• It is not easy to create a copy because its unique and high
accuracy.

5. 5
Type of Biometric?
1. Finger print
2. Palm veins
3. DNA
4. Iris recognition
5. Facial recognition
6. Voice recognition
7. Signature recognition
8. Palm print
9. Hand geometry
10.Retina scan
11.Ordure/Scent
https://en.wikipedia.org/wiki/Biometrics

6. 6
Comparison Between Biometric
Biometric Technology Accuracy Cost Device Required Social
Acceptability
DNA High High Test Equipment Low
Iris recognition High High Camera Medium -Low
Retina scan High High Camera Low
Facial recognition Medium -
Low
Medium Camera High
Voice recognition Medium Medium Microphone,
telephone
High
Hand geometry Medium -
Low
Low Scanner High
Finger print High Medium Scanner Medium
Signature recognition Low Medium Optic pen,
touch panel
High
http://kaitleencrowe.com/2015/01/22/biometric/
• Compared with other Bio Technologies, Finger Print is the best choice

7. Uniqueness Finger Skin Pattern
PANKANTI, S., PRABHAKAR, S., AND JAIN, A. K. On the individuality of fingerprints. IEEE Trans. Pattern Anal. Mach. Intell. 24 (August 2002), 1010–
1025. Available from: http://portal.acm.org/citation. cfm?id=605089.605091. 204, 212
• Human finger skin consists of friction ridges with pores.
• These ridges are formed in the ninth week of a fetal
development life, and remains the same all life long.
• A severely injured skin may be reconstructed to the same
as before.
• Identical twins have different fingerprints and no two
people have the same fingerprint.
• Every individual’s fingerprint is highly unique and suitable
for use as a form of authentication.

8. 8
Fingerprint Security
• Deny Intruders
– Higher Accuracy computation
• 97% will return correct results
• Prevent Re-construction of fingerprint data
– Image protection
• Minutiae is retrieved and template created
– Encrypted data
– Image destruction
• Cannot reconstruct the fingerprint from data
• Fake Fingerprints Detection
– Ignore Latent Print Residue
• Cannot steal from previous user
– Detect fake/amputated finger
• Sensors detect presences of
– Temperature, Pulse, Heartbeat sensors, Blood flow

9. 9
Technology Overview
Applications
PerformanceHardware/Software
Cost Analysis
Entrepreneur
Opportunity
Recommendation SystemFinger Print Technology

10. How Fingerprint are acquired?
Source: http://360biometrics.com/faq/fingerprint_scanners.php
Optical Sensor
Ultrasonic with RF Sensor
Optical Sensor
module
Capacitive Sensor
Thermal Sensor

11. Optical Fingerprint Sensors
Problem:
1. Scratched or dirty touch
surface can cause bad image
2. Easily fooled by fake finger
3. Bulky design, only suitable for
larger static installation
Function:
1. Reflected image of fingerprint captured by
camera from the underside of a prism.
2. Image is stored for comparison with
database.

12. Capacitive Fingerprint Sensing
http://appleinsider.com/articles/13/08/07/apple-inc-gets-its-
fingerprints-on-advanced-touch-sensor-appears-difficult-for-android-
to-copy
Ridge
Valley

13. Ultrasonic Fingerprint Imaging
http://www.sonavation.com/ultrasound-biometric-sensor/
https://youtu.be/FtKKZyYbZtw (1:30)

14. 14
Fingerprint Sensors Comparison
Optical Capacitive Ultrasound
Size Relatively big and
require camera
Can embed into
small devices
Can embed into
small devices
Method Image capture RF Field RF Field
Cost Middle Low High
Accuracy May be affected
by dirt or water
May be affected
by dirt or water
Will not be
affected by dirt or
water
Working Current 120 mA 200 mA 6 µA
Source: http://yourbusiness.azcentral.com/comparison-fingerprint-scanners-27754.html
http://artofcircuits.com/product/optical-fingerprint-sensor-module-fpm10a
http://www.techshinobiometrics.com/products/fingerprint-identification-products/fingerprint-oem-modules/
http://www.sonavation.com/ultrasound-biometric-sensor

15. Examples of Commercial Fingerprint
Scanners
http://perso.telecom-paristech.fr/~chollet/Biblio/Cours/Biomet/fribourg/maltoni_1.pdf
*The standard fingerprint image
resolution in law enforcement
applications is 500 pixels per inch
(ppi) Ppi = Dpi

16. 16
3 Levels of Fingerprint classification
1. Loops ,Arches , or Whorls
2. Individual characteristic (Minutiae)
http://shs2.westport.k12.ct.us/forensics/04-fingerprints/fingerprints_handout.htm

17. 17
3 Levels of Fingerprint classification
3. Pores and Ridges
1 Pores and Ridges: Fingerprint Matching Using Level 3 Features
by Jain, A; Yi Chen; Demirkus, M
2 Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features
by Jain, A.K; Yi Chen; Demirkus, M

18. 18
Basic Idea
• After these classification, a key is generated by the software algorithm.
• After finger print reader read your fingerprint, software will compare
with database.
http://gizmodo.com/apple-finally-explains-touch-id-security-in-detail-1532298901
Scan and Classify Generate a unique
user Key
Unlock access

19. 19
Cryptography
• There is two keys:
Public key
Private key (Fingerprint key)
• The basic idea is:
 Sender encrypts data with his receiver’s public key and send out.
 Receiver will use his/her private key to decrypt the data. No one
can decrypt without receiver’s private key!
http://gizmodo.com/apple-finally-explains-touch-id-security-in-detail-1532298901
Mathematically Linked

20. 20
Software Algorithm
• Software Classification
• http://shs2.westport.k12.ct.us/forensics/04-fingerprints/fingerprints_handout.htm
• http://www.bioelectronix.com/what_is_biometrics.html

21. Fingerprint Matching Software
• The most commonly used are:
1. Minutiae matching (commonly used)
2. Pattern matching
http://www.biometric-solutions.com/solutions/index.php?story=fingerprint_recognition
http://biometrics.mainguet.org/types/fingerprint/fingerprint_algo.htm

22. Advance Minutiae Based Algorithm (AMBA)
• Two processes
1. Feature Extractor
2. Matcher
http://www.supremasolution.com/

23. AMBA – Feature Extractor
• Feature Extractor
– Capture Image
– Enhance Ridge (Normalization, Local orientation estimation,
Local frequency estimation, Region mask estimation and
filtering)
– Extract Minutiae (Classification)
http://http://www.supremasolution.com/
http://www.cse.iitk.ac.in/users/biometrics/pages/finger.htm

24. AMBA - Matcher
• Matcher
– Used to match fingerprint
– Trade-off between speed and performance
– Group minutiae and categorize by 12 types
• Large number of certain type can result in faster searches
http://www.supremasolution.com/

25. Example: Apple ID touch
• Secure Enclave - using its microprocessor (A7)
to create protection to user’s data
• When device is locked:
– Data protection keys are wrapped (encapsulated)
– Data are not accessible
• When device is unlocked by the fingerprint
sensor:
– Data protection key are unwrapped (decapsulated)
– Iphone is unlocked and data is accessible
http://gizmodo.com/apple-finally-explains-touch-id-
security-in-detail-1532298901

26. How Fingerprint Biometric is used
• Enrollment
– Storing of fingerprint in
database
• Verification
– Known Identification of
person
– Compare the person’s
fingerprint in database
– One to one comparison
• Identification
–Unknown Identification of
person
– Search through database
for a match
– One to many comparison
Source: An Introduction to Biometric Recognition, Anil K. Jain, Fellow, IEEE, Arun Ross, Member, IEEE, and Salil Prabhakar, Member, IEEE, January 2004

27. 27
Technology Overview
Applications
PerformanceSoftware
Cost Analysis
Entrepreneur
Opportunity
Recommendation SystemFinger Print Technology

28. Optical Resolution vs Accuracy
http://biolab.korea.ac.kr/pubs/JainFpMatching_IEEEComp10.pdf
Jain, Feng, Nandakumar, Anil K. Kain, Jianjiang Fengm Karthik Nandakumar, 2010. Fingerprint Matching. Computer, 0018-9162, 36-44.
[a] http://itlaw.wikia.com/wiki/False_non-match_rate
[b] http://itlaw.wikia.com/wiki/False_match_rate
False Non-Match Rate (FNMR) is the failure of a biometric system to identify a biometric
subject or to verify the legitimate claimed identity of a biometric subject.
False Match Rate (FMR) is the proportion of the completed biometric non-match
comparison trials that result in a false match. [b]
False Positive Identification Rate (FPIR) occurs when the system finds a hit for a query
fingerprint that is not enrolled in the system.
False Negative Identification Rate (FNIR) occurs when it finds no hit or a wrong hit for
a query fingerprint enrolled in the system.

29. Image quality vs EER (4 software algorithm)
Image quality is important, better image, lower EER
Source: Incorporating Image Quality in Multi-algorithm Fingerprint Verification by Julian Fierrez-Aguilar, Yi Chen, Javier Ortega-Garcia, and Anil K.
Jain.
ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Campus de Cantoblanco 28049 Madrid,
Spain {julian.fierrez, avier.ortega}@uam.es. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48823,
USA
Equalerrorrate(thelower,thebetter)

30. Low Q Image Vs High Q Image (FRR & FAR)
Source: Incorporating Image Quality in Multi-algorithm Fingerprint Verification by Julian Fierrez-Aguilar, Yi Chen, Javier Ortega-Garcia, and Anil K.
Jain.
ATVS, Escuela Politecnica Superior, Universidad Autonoma de Madrid, Avda. Francisco Tomas y Valiente, 11 Campus de Cantoblanco 28049 Madrid,
Spain {julian.fierrez, avier.ortega}@uam.es. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48823,
Ideal Ideal

31. Sensor Duration vs FAR&FRR
http://www.neurotechnology.com/fingerprint-scanner-biometrika-fx-2000.html
Fingerprint Sensing Techniques, Devices and Applications Rahul Singh kingtiny@cs.cmu.edu 30th April 2003
Test data
1. Database of 100 users
(non-experts)
2. Low quality fingerprints
Efficiency
TASK SPEED_DEFAULT SPEED_FAST
Feature extraction 350 ms 260 ms
Matching 120 ms 47 ms
Identity verification 470 ms 307 ms
Accuracy:
Time taken
SPEED_DEFAULT SPEED_FAST
FAR FRR FAR FRR
0.3500 0.0049 (0.49%) 0.0005 (0.05%) 0.0032 (0.32%) 0.0009 (0.09%)
0.3750 0.0025 (0.25%) 0.0010 (0.10%) 0.0014 (0.14%) 0.0014 (0.14%)
0.4000 0.0011 (0.11%) 0.0014 (0.14%) 0.0005 (0.05%) 0.0020 (0.20%)
0.4250 0.0006 (0.06%) 0.0019 (0.19%) 0.0002 (0.02%) 0.0034 (0.34%)
0.4500 0.0004 (0.04%) 0.0026 (0.26%) 0.0000 (0.00%) 0.0049 (0.49%)
0.4750 0.0000 (0.00%) 0.0036 (0.36%) 0.0000 (0.00%) 0.0063 (0.63%)
FX2000 Optical Sensor Specification:
Resolution: 569 ppi,
Image Size: 296 x 570 pixels
Device size: 122 x 73 x 61mm
False Acceptance rate (FAR) is the
probability that the system incorrectly
authorizes a non-authorized person,
due to incorrectly matching.
False Rejection Rate (FRR) is the
probability that the system incorrectly
rejects access to an authorized person,
due to failing to match

32. 32
Microprocessor Improvements
• Size reduced, Speed increasing, Power consumption
http://www.futuretimeline.net/subject/computers-internet.htm
+http://www.singularity.com/charts/page61.html
http://www.androidauthority.com/smartphone-hardware-2015-405022/

33. Technology Enabler for Finger-print Authentication in
Mobile phone
• High-resolution sensors
–Capture higher resolution fingerprint data
• Micro-Processors
–Higher Processor Speed
• Storage Capacity
–Higher storage in mobile devices
• Smaller Form Factor
–Can be installed in mobile devices
GAFUROV, D., BOURS, P., YANG, B., AND BUSCH, C. Guc100 multi-scanner fingerprint database for inhouse (semi-public) performance and
interoperability evaluation. Computational Science and its Applications, International Conference (2010), 303–306. 203, 212

34. 34
Technology Overview
Applications
HardwareSoftware
Cost Analysis
Entrepreneur
Opportunity
Recommendation SystemFinger Print Technology

35. 35
Camera Based finger print sensor cost analysis
https://en.wikipedia.org/wiki/Touch_ID
http://www.imore.com/how-touch-id-works
http://biometrics.mainguet.org/types/fingerprint/fingerprint_sensors_manufacture.htm
Component Cost:
1. Finger Print sensor 53%
2. Cover glass 10%
3. Processing assembly 18%
4. Metal Rim 12%
5. F-PCB Component 7%
Key components:
1. laser-cut sapphire crystal
2. stainless steel detection ring
3. Touch ID CMOS sensor
4. Tactile Switch

36. 36
http://biometrics.mainguet.org/types/fingerprint/fingerprint_sensors_manufacture.htm
Key component
-- Finger Print Sensor Volume vs ASP
• Finger print sensor price drop rapidly with high demanding growth in future

37. 37
https://www.tractica.com/newsroom/press-releases/fingerprint-readers-in-mobile-devices-to-surpass-1-billion-unit-shipments-annually-by-2021/
Finger Print Sensor Market Demand
• High demanding forecast for fingerprint sensor, especially in Asian market.
Which can reduce fingerprint sensor manufacturing cost

38. 38
Key component
-- Display Cover glass demand
http://www.ledinside.com/intelligence/2014/6/wearable_devices_to_spur_sapphire_market_demands_in_2015_analyzes_ledinside
http://electroiq.com/blog/2015/07/smartphone-and-tablets-still-drive-demand-for-cover-glass-as-industry-looks-to-smart-watches-for-growth/
 The major market demand
growth is from smart phone
cover glass
 Display Cover glass demand
keep increasing in past 3
years and market demand is
keep increasing until 2019

39. 39
Key component
-- Sapphire Cost Forecast
http://www.i-micronews.com/component/hikashop/product/sapphire-applications-market-2015-from-led-to-consumer-electronic.html
• Sapphire is a major material for display cover, especially for hand phone camera cover and finger print
sensor cover. The overall price from different manufacturing process is keep going down.

40. Biometric Market Trends – Fingerprint Scanners
40Source: http://www.bloomberg.com/news/articles/2013-08-22/apple-iphone-rumor-boosts-biometrics-companies

41. Patents - Fingerprint Sensing
41
Fingerprint Sensors Patent Landscape
New strong IP enthusiasm and new players such as Apple are leaving their imprint on the market
Publication Jan. 2015

42. 42
Technology Overview
Applications
HardwareSoftware
Cost Analysis
Entrepreneur
Opportunity
Recommendation SystemFinger Print Technology

43. Consumer Acceptance to Fingerprint Authentication
• A Survey was conducted in 2010 on 278 Students on their
acceptance level to use fingerprint for authentication
– 58% of respondents had used fingerprint for authentication
(Notebook, facility access, etc.).
– Feedback on the likely services that they would use fingerprint
authentication
Biometrictechnologyinretailing:Willconsumersaccept fingerprintauthentication? Richard Clodfelter Department
ofRetailing,TheCollegeofHospitality,Retail,&SportManagement,UniversityofSouthCarolina,SC29208Columbia,UnitedStates

44. 44
Summary of Fingerprint Applications
-- Changing Lifestyle
• People are willing to use fingerprint technology instead of traditional way in
daily life, this is because fingerprint technology is reliable and convenient.
• Lifestyle is changing with fingerprint technology widespread used and hand
phone is a major base of this technology.

45. Without fingerprint With fingerprint
Mobile Phone based Applications
-- Unlock hand phone
• Since security concern, Apple and some other companies change hand phone
password from 4 number to 6 number which means users need longer time to unlock
their hand phone.
• Unlock your phone with fingerprint to save time. Hand Phone can be unlock while you
press home bottom
• Hand phone integrate reliable technology -- fingerprint function is a key to open the door
of new lifestyle.

46. Mobile Phone based Applications
-- Fingerprint technology in Banking
Bank Branch Bank Mobile APP
• People save time and easily to manage their bank account
by hand phone
• Banks can reduce No. of branches which means lower cost
for banks.

47. 47
https://www.linkedin.com/pulse/biometrics-banking-
hussain-
Mobile Phone based Applications
-- Fingerprint Technology in Banking
• Compared with other Biometrics
technologies, fingerprint
technology widely used in
banking
• Asian and US are largest market
in fingerprint banking.

48. 48
Mobile Phone based Applications
-- Mobile Bill Payment
AXS machine AXS online
• Without fingerprint, people don’t want to pay bill by mobile
phone, although some App have function of bill payment,
people are not willing to save credit card info in those App.
They have big concern on safety!
• With Fingerprint, people can pay bill by Mobile phone without
safety concern.

49. 49
Mobile Phone based Applications
-- Mobile Manage Stock
Buy/Sell at Stock market Buy/Sell on Handphone
• More easier to manage your Stock
account by hand phone. Fingerprint
replace password, Safer than password
based online Stock.

50. Mobile Phone based Applications
-- Online Shopping
Traditional shopping Online shopping
• Same concern on online shopping, people are not willing to purchase
stuff from online store.
• Fingerprint can solve this issue

51. 51
Applications on Automotive
https://www.youtube.com/watch?v=-PWbpZSBIGA
Car locker Car engine start
https://www.youtube.com/watch?v=xVXPpFpPWyU
• Use fingerprint to unlock Car or start engine are safer than current
practice, without car owner’s fingerprint, door unable to unlock and engine
unable to start.

52. 52
Applications on Security
-- Locker, Which one your want?
https://www.youtube.com/watch?v=b
mkrLvTJj1M
Door locker with Finger print sensor
Traditional door locker
People willing to change traditional locker to
fingerprint one, there are some benefits:
1. No need bring key
2. More safer than traditional locker

53. 53
https://www.youtube.com/watch?v=qVfddmIj_zU
USB storage with Finger print locker
Applications on Security
-- Data storage, Which one your want?
• Data storage with fingerprint function is
more safer for critical data storage.
Especially for individual privacy high
confidential information

54. 54
Applications on sports and exercise
-- Simulators
HealthcareSport simulator
Detect grip pattern:
1. Sportsman
2. Patients

55. 55
Technology Overview
Applications
HardwareSoftware
Cost Analysis
Entrepreneur
Opportunity
Recommendation SystemFinger Print Technology

56. 56
Entrepreneur Opportunity
Payment
$$$
Public Transport Convenient Stores
Vending
Machines
Computers

57. 57
Entrepreneur Opportunity
Gyms
Defence
Banks
Airports
Data storage
Homes/ offices
Automobiles

58. 58
Entrepreneur Opportunity
Sports
Newborn babies
Healthcare group

59. 59
Recommendation
• Protect information
• Passwords not reliable - easy to forget
• Fingerprints used for centuries
• Fingerprints are unique - can verify
• Accurate
• Many applications were developed
• Lot of business opportunities

60. Thank you

61. References
• http://info-tech.com.sg/fingerprint-
readers.htm?gclid=CJ230sCexMsCFdGKaAod7HMKzQ
• http://www.entrepreneur.com/article/168946
• http://airccj.org/CSCP/vol3/csit3504.pdf