BIOMETRICS LAB
Biometric Standards, Performance and Assurance Laboratory
Department of Technology, Leadership and Innovati...
AGENDA
• Introduction
• Methodology
• Results
• Lessons learned
• Next steps
INTRODUCTION
• Many factors can impact the
performance of a biometric system from
poor quality data [1]:
– Skin conditions...
MOTIVATION
• The efficiency of a biometric system is
important
• While investigating habituation of
biometric systems, the...
MOTIVATION
• We collect everyday – at what point do
you stop collecting from a subject?
– 3 samples?
– 6 samples?
– 9 samp...
MOTIVATION
• Number of subjects is important
• Must design protocol to keep costs low
while still processing as many subje...
QUESTIONS
• Are some fingers harder to collect?
– Do some take longer?
• Is the image quality of the first three any
diffe...
DATA
• Collection of multimodal
samples
• Only data from one
fingerprint sensor is be
used for analysis
• U.are.U 4500
• T...
DEFINITIONS
Term Meaning
SAS Successfully acquired sample,
synonymous with impression
Impression number Number given to ea...
BIOMETRICS LAB
Biometric Standards, Performance and Assurance Laboratory
Department of Technology, Leadership and Innovati...
METHODOLOGY
• 6 impressions/SAS were taken on each
finger with a maximum of 18 interaction
attempts to do so
• Fingers use...
METHODOLOGY
• An impression number was given to
each SAS in order for each finger
– Six impressions per finger, impression...
METHODOLOGY
• A number of approaches were used to
analyze the samples
– An analysis of the number of attempts
required for...
BIOMETRICS LAB
Biometric Standards, Performance and Assurance Laboratory
Department of Technology, Leadership and Innovati...
NUMBER OF INTERACTION
ATTEMPTS
• A comparison of the number of SAS’s to
the number of interaction attempts was
performed
•...
NUMBER OF ATTEMPTS
NUMBER OF ATTEMPTS
• No significant difference between the
fingers was found
• The right middle finger seems to have
the m...
DISTRIBUTION OF QUALITY
• A comparison of the first three collected
samples for any given finger to the last
three was per...
DISTRIBUTION OF QUALITY
• All of the samples were pushed through
a quality scoring algorithm, Aware WSQ
1000
• Scores a nu...
DISTRIBUTION OF QUALITY
DISTRIBUTION OF QUALITY
• A one-way ANOVA was used to compare
the first three SAS to the last three
• No finger showed a s...
MATCHING PERFORMANCE
• A comparison of the first three collected
samples for any given finger to the last
three was perfor...
MATCHING PERFORMANCE
• The samples were enrolled into a
minutiae-based matching
software, Megamatcher 4.3
• The first thre...
MATCHING PERFORMANCE
Finger First 3 vs First 3 Last 3 vs. Last 3 First 3 vs. Last 3
LI 0.0000 0.0000 0.0006
LM 0.3322 0.00...
MATCHING PERFORMANCE
• No improvements were noticed in
performance for any fingers except for
left middle
– The EER improv...
BIOMETRICS LAB
Biometric Standards, Performance and Assurance Laboratory
Department of Technology, Leadership and Innovati...
LESSONS LEARNED
• No issues were found when comparing
the number of interactions attempts
between fingers
– Though, right ...
BIOMETRICS LAB
Biometric Standards, Performance and Assurance Laboratory
Department of Technology, Leadership and Innovati...
NEXT STEPS
• Replicate this study on more sensors
• Attempt to observe habituation using
more than one visit
– Observe eff...
BIOMETRICS LAB
Biometric Standards, Performance and Assurance Laboratory
Department of Technology, Leadership and Innovati...
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(2013) Trade-off Between Impression Numbers and Attempt Numbers

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Presented at ICITA 2013, 8th International Conference on Information Technology and Applications, Sydney, Australia, 1 - 4 July, 2013

The amount of time taken to enroll or collect data from a subject in a fingerprint recognition system is of paramount importance. Time taken directly affects cost. A trade-off between number of impressions collected and number of interaction attempts allowed to submit those impressions must be realized. In this experiment, data were collected using an optical fingerprint sensor. Each subject submitted six successful impressions with a maximum of 18 interaction attempts. The resulting images were analyzed using three methods: the number of interaction attempts per finger, quality differences from the first three impressions to the last three impressions, and finally matching performance from the first three impressions to the last three impressions. The right middle finger seemed to have the most issues collecting as it required the most interaction attempts. Analysis was performed to show no significant differences in image quality or matching performance. However, after further analysis, a steady improvement was noticed from Group A to Group B in both image quality and matching performance.

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  • Good subjects, in theory, can submit three consistently good samples. Do we allow bad subjects to repeatedly submit samples when they may be submitting bad samples regardless. This will affect the time to collect, futhermore, the cost of collection.
  • Good subjects, in theory, can submit three consistently good samples. Do we allow bad subjects to repeatedly submit samples when they may be submitting bad samples regardless. This will affect the time to collect, futhermore, the cost of collection.
  • Bad subjects submitting three bad samples, will the sample improve with an additional.
  • Is there any difference in image quality and does that quality stop core/deltas from being visible?
  • (2013) Trade-off Between Impression Numbers and Attempt Numbers

    1. 1. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation 07/02/2013 Jacob A. Hasselgren, Stephen J. Elliott, Jue Gue TRADEOFF BETWEEN IMPRESSION NUMBERS AND ATTEMPT NUMBERS
    2. 2. AGENDA • Introduction • Methodology • Results • Lessons learned • Next steps
    3. 3. INTRODUCTION • Many factors can impact the performance of a biometric system from poor quality data [1]: – Skin conditions [2] – HBSI [3] – Associated meta-data [4] • Collect appropriate data and minimize time/error
    4. 4. MOTIVATION • The efficiency of a biometric system is important • While investigating habituation of biometric systems, the issue of the proper number of impressions collected and time arose
    5. 5. MOTIVATION • We collect everyday – at what point do you stop collecting from a subject? – 3 samples? – 6 samples? – 9 samples? • We cannot keep subjects forever due to time and costs
    6. 6. MOTIVATION • Number of subjects is important • Must design protocol to keep costs low while still processing as many subjects as possible • How many impressions should be collected from each subject? • How many attempts should be allowed? • Which fingers should be collected?
    7. 7. QUESTIONS • Are some fingers harder to collect? – Do some take longer? • Is the image quality of the first three any different from the last three? • Does the performance change when slicing groups taken from subjects? – ie. Do the first three impressions match well against the last three impressions of the same subject?
    8. 8. DATA • Collection of multimodal samples • Only data from one fingerprint sensor is be used for analysis • U.are.U 4500 • Taken from ongoing aging study in the BSPA Labs
    9. 9. DEFINITIONS Term Meaning SAS Successfully acquired sample, synonymous with impression Impression number Number given to each SAS, ranging from 1-6 Interaction attempt number Number given to each interaction attempt, whether it results in success or failure, ranging from 1-18
    10. 10. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation METHODOLOGY
    11. 11. METHODOLOGY • 6 impressions/SAS were taken on each finger with a maximum of 18 interaction attempts to do so • Fingers used: – Left index – Left middle – Right index – Right middle
    12. 12. METHODOLOGY • An impression number was given to each SAS in order for each finger – Six impressions per finger, impression numbers range 1-6 • An interaction attempt number was given to each interaction attempt in order for each finger – Max of 18 interaction attempts was given to submit 6 SAS’s, intearction attempt numbers range 1-18
    13. 13. METHODOLOGY • A number of approaches were used to analyze the samples – An analysis of the number of attempts required for each finger – Compare quality scores between designated groups (first three, last three) – Compare matching rates between same designated groups
    14. 14. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation RESULTS
    15. 15. NUMBER OF INTERACTION ATTEMPTS • A comparison of the number of SAS’s to the number of interaction attempts was performed • Each subjects submitted six SAS’s • Did any given finger require more interaction attempts than others?
    16. 16. NUMBER OF ATTEMPTS
    17. 17. NUMBER OF ATTEMPTS • No significant difference between the fingers was found • The right middle finger seems to have the most interaction attempts of all of the fingers collected – As well as the most variance
    18. 18. DISTRIBUTION OF QUALITY • A comparison of the first three collected samples for any given finger to the last three was performed to find differences in image quality
    19. 19. DISTRIBUTION OF QUALITY • All of the samples were pushed through a quality scoring algorithm, Aware WSQ 1000 • Scores a number of different metrics, with an overall quality score • This overall quality score was used in the following analysis
    20. 20. DISTRIBUTION OF QUALITY
    21. 21. DISTRIBUTION OF QUALITY • A one-way ANOVA was used to compare the first three SAS to the last three • No finger showed a significant difference Finger P-Value RI 0.155 RM 0.460 LI 0.090 LM 0.050
    22. 22. MATCHING PERFORMANCE • A comparison of the first three collected samples for any given finger to the last three was performed to find differences in matching performance
    23. 23. MATCHING PERFORMANCE • The samples were enrolled into a minutiae-based matching software, Megamatcher 4.3 • The first three SAS’s and last three SAS’s were enrolled separately • Equal error rates were used for results
    24. 24. MATCHING PERFORMANCE Finger First 3 vs First 3 Last 3 vs. Last 3 First 3 vs. Last 3 LI 0.0000 0.0000 0.0006 LM 0.3322 0.0000 0.1282 RI 0.0000 0.0000 0.0000 RM 0.0000 0.0000 0.0000
    25. 25. MATCHING PERFORMANCE • No improvements were noticed in performance for any fingers except for left middle – The EER improves from .3322 to .0000
    26. 26. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation LESSONS LEARNED
    27. 27. LESSONS LEARNED • No issues were found when comparing the number of interactions attempts between fingers – Though, right middle finger may require more attempts to collect impressions • To save time and unnecessary costs, it may not be practical to collect additional samples – No significant improvement was found after collecting three additional samples
    28. 28. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation NEXT STEPS
    29. 29. NEXT STEPS • Replicate this study on more sensors • Attempt to observe habituation using more than one visit – Observe effect of habituation on attempt numbers • Include time-on-task to get a true estimation on time required to collect SAS • Include hand dominance in interaction attempts
    30. 30. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation QUESTIONS? jahassel@purdue.edu

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